Digital Health Technologies Applied in Patients With Early Cognitive Change: Scoping Review

Yunhao Zhang; Xuejiao Zhu; Shulan Yang; Arkers Kwan Ching Wong; Xinming Chen

doi:10.2196/82881

. 2025 Dec 29;27:e82881. doi: 10.2196/82881

Digital Health Technologies Applied in Patients With Early Cognitive Change: Scoping Review

Yunhao Zhang ¹, Xuejiao Zhu ², Shulan Yang ^1,^✉, Arkers Kwan Ching Wong ³, Xinming Chen ⁴

Editor: Stefano Brini

PMCID: PMC12747421 PMID: 41461066

Abstract

Background

Digital health technologies (DHTs) have the potential to revolutionize the screening, diagnostic support, monitoring, and intervention for early cognitive change. However, the full spectrum of their application and the existing evidence base in this specific patient population have not been systematically delineated.

Objective

This study aimed to review and synthesize the applications, roles, and challenges of DHTs in patients with early cognitive change.

Methods

This scoping review was conducted in accordance with established methodological frameworks for scoping reviews and followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) and PRISMA-S (PRISMA Statement for Reporting Literature Searches in Systematic Reviews) guidelines. A systematic search was conducted across 5 electronic databases: PubMed, Embase, Web of Science, APA PsycINFO, and the Cochrane Library. The search covered the period from each database’s inception until September 30, 2025. Studies were selected, and data were extracted using the population-concept-context framework, focusing on digital health interventions for patients with early cognitive change.

Results

This scoping review identified 193 studies (from 8346 initial articles, screened down to 5623 after deduplication) evaluating DHTs for early cognitive change, with a marked publication surge post 2020. Studies predominantly focused on mild cognitive impairment and subjective cognitive decline. Among the 170 studies that reported the age of participants, the mean age of the participants was 74.09 (SD 7.98) years. Furthermore, six categories of DHTs emerged: (1) artificial intelligence or big data, (2) internet of things, (3) virtual reality or augmented reality, (4) robotics, (5) mobile apps or computerized cognitive training, and (6) telemedicine. Outcomes most frequently assessed included cognitive function, mental health, and feasibility. Notably, only 23 studies measured quality of life, with limited long-term (6‐12 months) follow-up. Physiological markers, social support, sleep quality, and self-efficacy were explored but less frequently.

Conclusions

DHTs demonstrate significant potential in the management of patients with early cognitive impairment, particularly playing crucial roles in screening, intervention, monitoring, and auxiliary diagnosis. This scoping review underscores that DHTs, through personalized interventions and continuous care, can effectively improve patient outcomes while innovatively incorporating the caregiver perspective. However, their practical application faces challenges in balancing technological complexity with user-friendliness. Future research needs to address five key issues: (1) the lack of long-term efficacy evidence, (2) insufficient coverage of individuals with subjective cognitive decline and caregiver populations, (3) a dearth of empirical evidence on the combined application of multiple DHTs, (4) the failure of personalized programs to fully account for individual differences, and (5) the absence of effective solutions to address data and ethical risks. There is an urgent need to establish a long-term efficacy evaluation system for DHTs through rigorous methodological validation.

Introduction

Background

Dementia arises from a range of diseases and injuries that primarily affect cognitive function, with Alzheimer disease (AD) representing the most common type [1]. The World Health Organization reports that over 55 million people worldwide live with dementia as of 2023, making it the seventh leading cause of death globally and a major contributor to disability and dependency among older adults [1]. The global economic cost of dementia was estimated at US $1.3 trillion in 2019 [1]. Given this substantial societal and financial burden, and in the absence of a definitive cure, effective disease management interventions are critically important [2].

According to the latest diagnostic and staging criteria for AD, the condition is categorized into 6 stages [3]. Stages 4-6 correspond to progressively worsening dementia [4]. The 0‐3 stages, including subjective cognitive decline (SCD) and mild cognitive impairment (MCI), are often regarded as the initial or transitional phases in the progression toward dementia, including AD [5]. Compared with cognitively normal older adults, individuals with SCD have twice the risk [6], and those with MCI have 4 times the risk of developing dementia [7]. These stages are critical for early intervention. However, research by Thoits et al [8] indicated that many patients are not diagnosed until the later stages of the disease, resulting in missed opportunities for early treatment and a greater burden on families [9]. Therefore, prioritizing early identification, intervention, and ongoing monitoring is essential. This scoping review collectively refers to the 0‐3 stages as the early cognitive change stages, to explore the effectiveness of early identification and interventions, and the potential of these measures in delaying disease progression and improving patients’ quality of life.

In recent years, advancements in information and communication technology have significantly enhanced the potential of digital health technologies (DHTs) in cognitive care. Compared with traditional treatments, digital health provides greater long-term benefits by incorporating smart applications, virtual and augmented reality (AR), artificial intelligence (AI), telemedicine, mobile health, chatbots, and the internet of things (IoT) [10]. These tools enable precise identification of cognitive changes and deliver personalized rehabilitation, while real-time data allows health care professionals to optimize interventions and improve patient outcomes [11,12].

Current methods for identifying and intervening in cognitive decline are diverse, with numerous DHTs emerging as alternatives or supplements to traditional cognitive therapy. These technologies have been widely studied; however, the research and development efforts are often fragmented. Existing reviews tend to focus on specific DHTs used in patients with MCI or AD, such as AI [13], virtual reality (VR), and mobile apps [14]. While these studies contribute to understanding the application of individual tools in managing early cognitive change and dementia and promote technological optimization, they fail to provide a comprehensive overview of the broader application landscape of DHTs across the spectrum of early cognitive change.

Research Problem and Aim

A comprehensive understanding of DHTs in early cognitive change remains incompletely developed, largely due to a fragmented and narrow evidence base. Previous reviews have predominantly addressed limited efficacy questions, failing to provide a consolidated overview of the broader application landscape. To address this gap, this scoping review was designed to systematically map the entire field. This scoping review aims not only to catalog the diverse types of DHTs, the application scenarios, and target populations but also to synthesize key challenges identified across the literature. By doing so, it seeks to establish a foundational understanding for future research and to inform the integration of DHTs into clinical and health care systems. This scoping review provides a systematic synthesis of the evidence on DHT applications in early cognitive change and a clear delineation of prevailing challenges.

Methods

Overview

This scoping review followed the framework outlined by Arksey and O’Malley [15] with an extended version by Levac et al [16], and was reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) [17] and PRISMA-S (PRISMA Statement for Reporting Literature Searches in Systematic Reviews) [18,19], with the completed PRISMA-ScR checklist (Checklist 1) and PRISMA-S checklist (Checklist 2).

Identification of the Relevant Studies

A comprehensive 3-stage search strategy was implemented. First, preliminary searches in PubMed and Embase databases were conducted to explore the application of DHTs in patients with early cognitive change. This scoping review then analyzed the text words in the titles and abstracts of the retrieved records, along with their relevant index terms. Second, based on this analysis of frequently used terms and concepts, a systematic search was conducted across 5 electronic databases: PubMed, Embase, Web of Science, APA PsycINFO, and the Cochrane Library. Each database was searched individually from its inception until the final search date of September 30, 2025; all searches were last updated and rerun on this date to ensure timeliness. The complete search strategies are provided in Multimedia Appendix 1. Third, the reference lists of all identified studies were screened, and a supplementary search was conducted via Google Scholar to locate additional relevant publications. For studies whose full text was unavailable, this scoping review attempted to retrieve them by contacting the corresponding authors, relevant experts, manufacturers, or through other available channels. The search strategy was developed independently for this review and was not adapted from any previously published work.

Study Selection

The inclusion and exclusion criteria were developed based on the population-concept-context framework.

Population: According to the latest AD diagnostic criteria [3], this scoping review included patients in stages 0 to 3, including those with SCD, MCI, or preclinical AD, as well as their caregivers, including family members or spouses.
Concept (intervention): This scoping review focused on studies involving various types of DHTs, including IoT, AI, VR, AR, robotics, data science, big data, smartphone apps, computer applications, and telemedicine. Studies that did not involve interaction with DHTs, such as computer applications that merely involve watching stimuli, were excluded.
Concept (outcome): Outcome measures related to the intervention were included, whether assessed through self-reporting or objective assessments conducted by clinicians, researchers, or caregivers. These measures included cognitive function, physical function, mental health, sleep quality, quality of life, physiological markers, sociability, task performance, feasibility, model evaluation metrics or diagnostic accuracy, caregivers’ burden, and others. Studies that focused solely on the architecture or implementation of devices, without assessing the impact of the intervention on users, were excluded.
Context: Only articles published in English were included. Eligible study types included randomized controlled trials (RCTs), quasi-experimental studies, cohort studies, case-control studies, cross-sectional studies, case reports, and descriptive studies. Studies such as reports on DHTs without patient outcomes, dissertations, study protocols, trial registrations, conference abstracts, editorials, and letters were excluded.

Studies retrieved from the databases were filtered according to the eligibility criteria outlined above. The requirements were based on the population-concept-context framework, as this scoping review aimed to examine the scope and outcomes of various DHTs. Only studies in which the keywords corresponded to the population, intervention, and outcome were included, while studies that mentioned these keywords only in the background of their research were excluded.

Search results from each database were merged using EndNote X9 (Clarivate). After duplicates were removed, 3 independent researchers (YZ, SY, and XC) screened the studies based on titles and abstracts and reviewed the full texts of the remaining studies according to the eligibility criteria. Any disagreement between the researchers was resolved through discussion.

Data Extraction

A data extraction form was developed based on the Joanna Briggs Institute methodology guidelines for scoping review [20]. The form was piloted using 5 randomly selected articles and refined before full implementation. The extracted data included authors, year of publication, study design (eg, RCT, quasi-experimental studies, cohort studies, case-control studies, cross-sectional studies, case reports, descriptive studies, and qualitative research), participant characteristics (including demographic features and stages of cognitive impairment), type of DHTs, and outcome measures. Furthermore, 2 independent reviewers (YZ and XC) conducted the data extraction, with a senior reviewer (SY) consulted to resolve any discrepancies.

Collating, Summarizing, and Reporting the Findings

Based on the extracted data, a descriptive analysis was performed to examine trends and the distribution of DHTs across different application purposes, such as screening, diagnostic aid, intervention, and monitoring. The outcomes related to DHTs used in early cognitive change were evaluated, and studies were categorized by their application purposes. The findings were then summarized and presented descriptively through tables and figures to address the review questions.

Results

Literature Search

The detailed study selection process is presented in Figure 1. A total of 8340 articles were identified, and 5620 were retained after excluding duplicates. According to the eligibility criteria, 5309 articles were removed during title and abstract screening, 15 articles could not be accessed, and 100 were excluded after full-text review by 2 researchers (YZ and XC). The final selection for this scoping review included 193 articles [21-213] (Figure 1, Checklist 1).

Characteristics of the Included Studies

The publication trend (Figure 2) of DHTs applied to early cognitive change showed a notable increase from 2020 onwards. Although the first relevant RCT [108] was published in 2009, the number of studies on DHTs remained relatively stable until 2020. Subsequently, there was a marked surge in publication volume, with 26 studies [33,39,43,48,51,57,61,62,68,75,76,78,82,86,92,98,102,134,136,149,155,162,167,168,170,181] published in 2021, 21 studies [21,25,32,38,42,60,65,72,93,95,100,113,117,119,120,132,141,144,176,180,183] in 2022, 33 studies [24,26,27,35,36,41,44,46,47,56,59,66,69,80,81,88,99,106,114,128-131,138,142,153,157,161,163,173,185,190,202,undefined,undefined,undefined] in 2023, 17 studies [23,97,101,110,121,123,140,143,145,146,154,166,172,197,200,201,203] in 2024, and 23 studies [79,124,186-189,191,193-196,198,199,204-213,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined] in 2025. Experimental studies constituted the majority (157/193) of the research identified as of September 2025. Among these, case report, case-control study, longitudinal study, and mixed method study each constituted only 1 included study [76].

The studies predominantly focused on patients with early cognitive change, particularly those with MCI and SCD. The majority of the studies focused on patients with MCI (110/193). Only 10 studies [30,33,46,55,68,75,82,133,138,167] examined patients with SCD, with 4 studies [30,75,82,138] focusing solely on this group. Only 6 studies [65,91,92,154,193,196] included informal caregivers of the patients. Regarding the age criteria for inclusion, the age range across all studies spanned from 50 to 96 years. Some studies did not use age as an inclusion or exclusion criterion; instead, they used cognitive function scores (such as Mini-Mental State Examination and Montreal Cognitive Assessment) for participant screening. Based on the available data from studies that reported mean age, the overall mean age of participants across the included studies was calculated to be 74.09 (SD 7.98) years.

Type of DHTs Implemented in Patients With Early Cognitive Change

DHTs are increasingly being used in patients with early cognitive change. Given that AI and big data technologies are data-driven, while smartphone apps and computer applications serve as application-based tools, this scoping review categorized these technologies into 6 main types: AI or big data, IoT, VR or AR, robotics, mobile apps or computerized cognitive training, and telemedicine. The distribution of research subjects related to DHTs is illustrated in Figure 3, while the development trends of various DHTs are depicted in Figure 4.

Research primarily focused on mobile apps or computerized cognitive training, with 89 studies [24,25,28,30,32,40-42,44,46,57-59,65,67,69,77,78,80-82,84,85,94,96,98,99,101,103-105,107-117,120-122,124-126,128-131,133,138,140,141,145,147-152,154,156,159,162,164,170-172,180,181,188,189,193,196,197,199,201-206,208-211,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined] examining its impact. The majority of these studies used computer programs or mobile apps (78/89), while a smaller number used gaming consoles (8/89) or web-based platforms (3/89). It is noteworthy that in specialized studies targeting individuals with SCD, half of them used mobile apps or computerized cognitive training interventions. These data indicate that smartphone apps and computer applications not only possess broad applicability in the field of cognitive intervention but, due to their user-friendliness, have also become the preferred technological medium for populations experiencing early cognitive changes such as SCD.

VR research also expanded, with 63 studies [21,26,27,33,36,37,43,50-56,60,68,71,74-76,83,86-89,100,106,118,119,123,127,132,134,135,137,142,144,153,155,158,160,165,166,169,173-179,182-185,187,192,194,195,200,207,212,213,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined,undefined], particularly since 2017, VR technology has been applied in a variety of scenarios, including virtual cycling, road crossing simulations, and virtual supermarkets, all aimed at enhancing cognitive training through immersive environments. Among these apps, the virtual supermarket is the most commonly studied scenario, with 19 studies [33,36,43,50-52,54-56,68,75,86,89,119,127,142,144,175,176,undefined,undefined,undefined,undefined] dedicated to its construction or validation. Some studies, such as the one by Afifi et al [21], integrated multiple VR activities, such as virtual adventures, recalling life stories, and virtual photo videos, to target various cognitive domains to improve overall cognitive function.

A total of 14 studies [25,45-49,61-63,81,102,139,157,198,undefined,undefined,undefined,undefined,undefined,undefined] on AI or big data primarily implemented machine learning techniques (eg, support vector machines, random forests, and deep learning) to detect early cognitive change and personalize interventions. Furthermore, 2 studies [48,180] also applied natural language processing to enhance detection and intervention precision.

In robotics, 10 studies [22,34,70,72,73,161,167,168,186,191] explored social assistance and gait training; 7 studies [34,70,72,73,167,168,186] focused on humanoid robots designed to improve social skills and cognitive function, while 1 study [22] developed omnidirectional mobility robots for physical rehabilitation [22].

IoT research is limited, with 11 studies [23,26,31,66,90,91,95,97,153,198,209] on patient monitoring via devices, such as wearable cameras, wrist devices, and smart home sensors. These technologies enable continuous, comprehensive monitoring of patients’ cognitive and physical states [23].

Telemedicine saw a rise in research, with 14 studies [24,29,35,38,39,64,79,92,93,136,143,146,163,190] conducted, particularly after 2020. Some studies have integrated various DHTs to enhance telemedicine interventions. For example, the study by Nousia et al [24] combined an app-based cognitive training (smartphone apps or computer applications) system with telerehabilitation, while Fristed et al [25] explored the use of smartphones with deep learning algorithms to improve recall tasks. Additionally, Tian et al [26] incorporated IoT devices and VR interventions to create a more immersive and effective therapeutic approach.

Outcomes of DHTs in Patients With Early Cognitive Change

The included studies used a diverse array of cognitive assessment tools to measure various cognitive domains in patients with early cognitive changes, encompassing overall cognitive function, memory, executive function, attention, processing speed, and language abilities. The selection of assessment tools for cognition varied across different studies. Traditional assessment tools, such as the Mini-Mental State Examination, Montreal Cognitive Assessment, or Trail Making Test, were the most commonly used. Additionally, some studies collected data on gait, speech speed, and facial expressions and developed novel digital cognitive assessment tools. Compared with traditional tools, these digital technology-based tools minimize examiner bias and practice effects through standardized administration and adaptive item pools, enabling long-term, frequent home-based monitoring. Notably, a small subset of studies determined patients’ cognitive function based on observational descriptions provided by family members.

Negative emotions, such as depression, anxiety, and apathy, are often linked to reduced cognitive function [27]. The research by Afifi et al [21] explored how VR technology enabled adult offspring to remotely participate in parental care by recreating familiar locations for shared activities via VR. The study found that VR not only enhanced the psychological well-being and relational dynamics between older adults and their family members but also improved the quality of life for older adult patients while reducing caregivers’ guilt. Chandler et al [28] evaluated 5 interventions (yoga, computerized cognitive training, health education, support groups, and memory support system) and demonstrated that persistent computerized cognitive training for 12 months significantly reduced anxiety levels while enhancing self-confidence. Furthermore, wearable devices were used to track neuropsychiatric symptoms, with findings suggesting a relationship between anxiety, sleep quality, and cognitive outcomes [23].

Sleep quality was often monitored using IoT and wearable devices in many studies, revealing a connection between sleep and cognitive improvement [29,30]. Notably, studies examining sleep-related issues consistently assessed mental health alongside sleep metrics [23,31].

Feasibility outcomes—assessing factors such as usability, adherence, and patient satisfaction—were generally positive, with high participation rates, especially for interactive interventions [32]. However, challenges like mild VR-induced dizziness [33], low engagement in robot-assisted training [34], and poor telemedicine connectivity [35] were noted but were expected to diminish over time [36]. Overall, VR-induced vestibular symptoms, connectivity issues, and digital literacy gaps among the older adult population were reported when discussing the negative outcomes when applying DHTs.

Physical function was assessed using indicators including balance, gait, walking speed, muscle strength, flexibility, activities of daily living (ADLs), and fall risk. Studies showed that gait changes are often used to screen for early cognitive change, and interventions using VR or telemedicine could significantly improve balance [37], gait [38], and reduce fall risk [39]. ADLs, key in assessing physical function, are divided into basic [40,41] and instrumental [42,43] tasks, with most studies focusing on the more complex instrumental ADLs. The results indicate that the ability to perform ADLs can be improved through intervention.

Several studies developed screening tools using DHTs to address the limitations of current methods. These studies often used model evaluation metrics such as sensitivity, specificity, accuracy, area under the curve, F₁-score, and precision as outcome measures. Data sources included voice [25,44-48,undefined,undefined,undefined,undefined] and video recordings [49], facial expressions [47], behaviors in VR [43,50-56,undefined,undefined,undefined,undefined,undefined,undefined], app usage [57-61], gait tests [62,63] (stride time, step length, speed, and support times), and general scales. Most studies used machine learning for data analysis, while others used simpler statistical approaches, like logistic regression [43,53,59-61,64,65,undefined,undefined].

Task performance was commonly used as an outcome measure in VR and smartphone app and computer application interventions, and it was typically assessed through metrics such as completion time, accuracy, and error rate in memory tasks. This outcome measure was highly flexible, offering immediate feedback that helped patients self-adjust and allowed researchers to observe the direct effects of the intervention.

Cognitive interventions typically aim to improve quality of life by enhancing cognitive abilities. Twenty-three studies [21,28,29,37,38,40,42,65-67,94,99,104,105,111,115-117,134,138,191,197,211,undefined,undefined,undefined,undefined] used quality of life as an outcome indicator. While most studies indicated that cognitive improvements are associated with better quality of life, this relationship is not always significant [66]. It is important to note that only 3 studies [28,65,67] investigated the quality of life at 6 or 12 months postintervention, with the majority focusing on shorter follow-up periods (3‐4 months), leaving the long-term effects largely unexplored.

Other outcome measures include physiological markers, social connectedness, self-efficacy, and personal habits. Physiological markers are typically assessed using wearable devices, such as an electroencephalogram [68] and magnetic resonance imaging [69]. Although less explored, DHTs showed promise in reducing social isolation and improving social connectedness [70]. Self-efficacy [214] and personal habits [71] were also investigated as indicators of intervention success.

Discussion

Principal Findings

Based on the scoping review of the application trends of DHTs in populations with early cognitive changes, this scoping review found that the number of relevant studies increased significantly since 2020. The technical types covered 6 major categories, including AI or big data and VR or AR. However, this scoping review revealed an imbalance in the target population: patients with MCI were the main focus, while insufficient attention was paid to individuals with SCD and caregivers. The outcome measures focused on cognitive function, mental health, and feasibility. Building on the study results, this scoping review discussed and sorted out the application scenarios, aiming to provide a comprehensive perspective for health care professionals, policymakers, and technology developers to guide future research and innovation in this field.

The Application of Various DHTs in Early Cognitive Change

The discussion section of this scoping review focuses on the current application status and challenges of DHTs in patients with early cognitive changes, revealing the technology characteristics and clinical needs through systematic comparison.

Although robotic technology can enhance motor rehabilitation and assist in diagnosis through physical interaction [22,72,73,215], its high cost and the risk of replacing human interaction [34] stand in stark contrast to the multisensory immersion advantages of VR technology. VR technology can more naturally activate the episodic memory of patients with early cognitive changes by reconstructing virtual environments (such as recreating home scenarios, virtual grocery shopping in extended time, etc) [74]. When combined with personalized intervention strategies, it can enhance self-efficacy [75]. However, it should be noted that the motion sickness induced by VR may offset some of its cognitive benefits [76]. This complementary nature of “blending the virtual and the real” suggests that future research could explore the potential of hybrid systems combining robotics and VR.

Mobile apps or computerized cognitive training interventions encompass software that runs on computers, mobile phones, tablets, or gaming consoles. These tools are user-friendly and easily accessible. However, research findings indicate that their effectiveness hinges on patients’ levels of engagement and technological familiarity [77]. Taking Wii Sports (Nintendo EAD) games as an example, their cognitive training efficacy not only depends on the difficulty gradient of the game design but is also significantly correlated with patients’ digital literacy levels [32,78]. It is recommended that, in the future, before implementing interventions using smartphone apps or computer applications, a comprehensive assessment should be conducted on patients. This assessment should screen patients’ baseline cognitive abilities, evaluate their operational proficiency with digital technologies, and track their continued willingness to participate after the intervention, thereby forming a closed-loop intervention pathway.

Telemedicine demonstrates cost-effectiveness advantages in remote areas [29,38]. However, its effects have a double-edged nature. While it can overcome geographical barriers, it may potentially exacerbate anxiety and depression in certain scenarios [29,79,80]. The IoT technology enables continuous health monitoring through multidevice collaboration, coupled with rapid analysis of digital biomarkers by AI, showing immense potential in the detection of early cognitive changes [25,47,62]. Nevertheless, the reliance of AI on large datasets and challenges in interpretability restrict its application effectiveness in resource-constrained environments [81].

Future research should focus on technology integration and the practice of the 3C principles: compatibility (evaluating the match between technological interfaces and patients’ physiological characteristics), continuity (dynamically adjusting intervention programs in accordance with disease progression), and cost-effectiveness (quantifying the ratio of technological investment to clinical benefits). This integrated deployment strategy not only addresses the need for improvement regarding the current inadequacy in cross-comparative studies of DHTs but also establishes a complete logical chain from current situation analysis to decision-making frameworks.

The Potential Application of Specific DHTs to Aid Those With Cognitive Complaints

Screening

The goal of screening is to detect health issues early, facilitating timely intervention and halting disease progression [216]. IoT and AI leverage wearable devices and smart home sensors for continuous monitoring of cognitive and behavioral patterns, such as gait, sleep, and activity levels [31]. AI algorithms can identify early cognitive change [25]. This passive monitoring enhances early screening capabilities. Concurrently, telemedicine apps and VR-based tests, like the virtual supermarket test, actively assess cognitive function through remote interactions and simulated environments [56,82]. These combined passive and active approaches offer a comprehensive strategy for the early detection of cognitive decline.

Diagnostic Support

This scoping review explored the role of DHTs in assisted diagnosis, which enhances diagnostic efficiency and supports clinical decision-making without replacing physicians’ judgment. VR techniques, such as the Virtual Supermarket Test [68], Virtual Goal Orientation [74], and Virtual Fire Drill [83], are instrumental in assessing cognitive function, mental health, and physiological markers, aiding in the distinction between patients with SCD, MCI, and AD. Social robots were used to facilitate the diagnosis of cognitive changes in patients with MCI [72], while apps were developed to automatically analyze speech and language patterns in individuals with MCI [46]. Furthermore, an internet-based telerehabilitation system was used for diagnosing swallowing disorders in patients with MCI [64]. These digital diagnostic aids excel in processing complex data and presenting comprehensive results to health care professionals, thereby improving diagnostic accuracy and reducing physician workload.

Intervention

The application of DHTs in interventions for early cognitive change aims to slow or improve cognitive decline, enhancing patients’ quality of life and functional independence.

Among these technologies, smartphone apps and computer applications are widely used, offering individualized programs that target various cognitive domains such as memory, attention, and executive function. These programs, which include somatic games [84], computer applications [40], and story recall exercises [85], are designed to meet the specific needs of each patient.

VR is another promising tool for cognitive training, providing immersive environments that simulate real-world scenarios, such as virtual supermarket shopping [86], driving [71], and road crossing [87]. VR offers multisensory stimulation, enhancing memory, attention, spatial navigation, and executive functions by integrating visual, auditory, and tactile feedback [88]. Unlike traditional methods, VR is more interactive and adaptive, allowing task adjustments and providing immediate feedback, which significantly boosts training effectiveness [88,89].

Telemedicine, which facilitates remote diagnosis and rehabilitation, enables patients to access health care services from home while maintaining interaction with health care providers. By leveraging videoconferencing, remote monitoring, and online consultations, telemedicine allows for real-time assessment, treatment plan adjustments, and cognitive training via digital platforms like smartphone apps and computer applications. This approach offers essential support, especially for patients with mobility impairments [24].

Robotics also plays a key role in slowing cognitive decline. Social robots, which assist with cognitive training and provide emotional support, are particularly valuable. These robots engage in verbal interactions, supporting language training, offering daily reminders, and assisting with tasks like medication management and exercise routines. Such functionalities increase the acceptability of robots among patients and their families [22,34].

In summary, the integration of various DHTs offers significant promise in addressing early cognitive change, enhancing training effectiveness, and improving the overall care experience for patients.

Monitoring

Monitoring aims to continuously track changes in the individual’s health and cognitive function, allowing for the early identification and management of potential issues. Long-term data collection and analysis provide insights into the progression of cognitive impairment and treatment effectiveness, enabling the development of more personalized and adaptive care plans. Only 4 studies [23,90,91,95] on monitoring were identified, all focused on IoT and wearable devices. For instance, environmental sensors continuously track conditions like light, noise, temperature, humidity, carbon dioxide, and air quality to identify factors affecting cognitive function and behavior [23]. Wearable sensors can monitor physiological signals, such as heart rate, heart rate variability, and electrodermal activity, during training sessions to assess the impact on cognitive performance and stress response [90]. Additionally, the LifeLog Recording wearable camera automatically captures images of daily activities, helping monitor behavioral changes and supporting cognitive training programs to improve patients’ situational memory [91].

Importance of the Caregiver’s Role

Due to limited health care resources and the growing demands of an aging population, many studies advocate for home-based caregiving to alleviate pressure on the health care system [217]. Informal caregivers play a crucial role in supporting patients with cognitive changes, yet they often face emotional stress, mental health challenges, and significant physical, psychological, and financial burdens [218-221]. Despite these challenges, the focus on informal caregivers remains limited, particularly for those caring for patients in the early stages of cognitive decline. Research has typically concentrated on more advanced stages of dementia, leaving fewer studies on caregivers in the earlier stages [222].

In the included studies, informal caregivers included spouses [67,92], children [21], siblings, and other family members [93,214]. A study by Lai et al [93] defined the informal caregiver as family members who provide daily care tasks without compensation, while Beentjes et al [214] described them as individuals living with or visiting the patient at least twice a week. Although definitions of informal caregivers varied, they generally referred to family members providing unpaid care. However, 3 studies mentioned informal caregivers without offering a clear definition, which could introduce ambiguity in interpreting the findings.

Different DHTs have demonstrated improvements for informal caregivers on multiple levels. For instance, the study by Lai et al [93] found that telemedicine interventions significantly reduced caregiver stress and were widely accepted by caregivers. Beentjes et al [214] used FindMyApp in their study to provide personalized app recommendations, not only lowering the technical barrier to use for caregivers with lower educational levels, but also transforming instrumental technology into a continuous learning platform for the development of caregiving competencies by sending relevant courses and guidelines weekly. The VR intervention in the study by Afifi et al [21] not only reactivated patients’ episodic memory by reconstructing shared virtual family scenes, but also transformed the technology into a medium for intergenerational emotional connection through a collaborative “patient-led, caregiver-followed” model. This collaborative narrative process significantly improved the mental health of both parties [21]. The study by Ghani et al [65], using the web platform, helped caregivers manage patients’ daily activities more effectively, such as medication and appointments. Although the web platform was expensive and less effective for patients with MCI, it proved cost-effective and beneficial for improving caregiver quality of life.

However, digital interventions may have unintended negative consequences. Lai et al [93] noted that telehealth interventions could weaken family dynamics, reducing problem-solving, communication, and emotional support. Additionally, not all studies showed significant improvements in caregiver outcomes. For instance, Ghani et al [65] found improvements in caregivers’ burden, but the difference was not statistically significant compared with the control group.

Future research may consider exploring digital technology-based care communities, enabling 3-dimensional collaboration among patients, caregivers, and medical teams through DHTs. For instance, distributed health records built on blockchain technology can facilitate secure cross-platform sharing of care logs; meanwhile, an analysis module integrated with AI computing can monitor patients’ emotional fluctuations in real time and trigger early warnings. Such a technological ecosystem not only supports daily care but also transforms challenges into opportunities for the whole family’s collective growth.

Limitations

This scoping review systematically uncovered five specific research gaps in the application of DHTs for early cognitive changes: (1) long-term studies are scarce, as most research is constrained by short-term follow-up designs, making it difficult to capture long-term effects; (2) representation of patients with SCD is notably inadequate, with coverage far lower than that of individuals with MCI; (3) research on the integration of multiple DHTs is still in its early exploratory stages, lacking empirical validation; (4) personalized adaptation designs often overlook individual difference parameters such as disease progression rate, comorbidities, and user preferences; and (5) despite involving sensitive biological data, ethical and privacy risks associated with AI and IoT applications largely remain at the theoretical discussion stage, lacking empirical balancing solutions. The identification of these gaps clearly pointed out a crucial direction for future research to transition from a “technology-driven” approach to a “patient-centered” paradigm.

Conclusions

This scoping review makes distinct contributions to the literature by systematically mapping the landscape of DHTs in early cognitive change. This scoping review’s primary contribution is threefold. First, it synthesizes evidence to reveal the significant potential of DHTs across the care continuum—from screening and diagnosis to intervention and monitoring—while critically incorporating the often-overlooked caregiver perspective, thereby offering a more holistic understanding. Second, it moves beyond a generic evaluation to delineate the differentiated clinical value of various DHTs, highlighting their unique strengths in delivering personalized interventions and maintaining continuity of care. Finally, a central challenge undermining the practical application of DHTs is the difficulty in balancing technological sophistication with user-friendliness. Looking forward, future research should focus on generating robust long-term evidence, broadening the scope to include underrepresented groups like SCD and caregivers, and developing strategies for the integrated, ethical, and truly personalized implementation of DHTs.

Supplementary material

Multimedia Appendix 1. Search strategies.

jmir-v27-e82881-s001.xlsx^{(44.6KB, xlsx)}

DOI: 10.2196/82881

Checklist 1. PRISMA-ScR checklist.

jmir-v27-e82881-s002.docx^{(57.4KB, docx)}

DOI: 10.2196/82881

Checklist 2. PRISMA-S checklist.

jmir-v27-e82881-s003.docx^{(16.8KB, docx)}

DOI: 10.2196/82881

Abbreviations

AD: Alzheimer disease
ADL: activity of daily living
AI: artificial intelligence
AR: augmented reality
DHT: digital health technology
IoT: internet of things
MCI: mild cognitive impairment
PRISMA-S: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement for Reporting Literature Searches in Systematic Reviews
PRISMA-ScR: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews
RCT: randomized controlled trial
SCD: subjective cognitive decline
VR: virtual reality

Footnotes

Funding: This scoping review was partly funded by the Zhejiang Provincial Medical and Health Science and Technology Plan (2024KY004). The project leader, serving as the corresponding author, was responsible for comprehensive quality oversight throughout the manuscript development process.

Data Availability: The scoping review was based on data from peer-reviewed publications. All extracted data relevant to the study aims are included within the manuscript and appendices.

Conflicts of Interest: None declared.

References

1.Dementia. World Health Organization. [31-09-2025]. https://www.who.int/news-room/fact-sheets/detail/dementia URL. Accessed.
2.Cummings JL, Tong G, Ballard C. Treatment combinations for Alzheimer’s disease: current and future pharmacotherapy options. J Alzheimers Dis. 2019;67(3):779–794. doi: 10.3233/JAD-180766. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Alzheimer’s disease facts and figures: special report 2022. Alzheimer’s Association. 2022. [31-09-2025]. https://www.alz.org/media/Documents/alzheimers-facts-and-figures-special-report-2022.pdf URL. Accessed.
4.Jack CR, Andrews JS, Beach TG, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association workgroup. [27-11-2025];Alzheimer’s & Dementia. 2024 Aug;20(8):5143–5169. doi: 10.1002/alz.13859. https://alz-journals.onlinelibrary.wiley.com/toc/15525279/20/8 URL. Accessed. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med. 2004 Sep;256(3):183–194. doi: 10.1111/j.1365-2796.2004.01388.x. doi. Medline. [DOI] [PubMed] [Google Scholar]
6.Mitchell AJ, Beaumont H, Ferguson D, Yadegarfar M, Stubbs B. Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta-analysis. Acta Psychiatr Scand. 2014 Dec;130(6):439–451. doi: 10.1111/acps.12336. doi. Medline. [DOI] [PubMed] [Google Scholar]
7.Jia L, Quan M, Fu Y, et al. Dementia in China: epidemiology, clinical management, and research advances. Lancet Neurol. 2020 Jan;19(1):81–92. doi: 10.1016/S1474-4422(19)30290-X. doi. Medline. [DOI] [PubMed] [Google Scholar]
8.Thoits T, Dutkiewicz A, Raguckas S, et al. Association between dementia severity and recommended lifestyle changes: a retrospective cohort study. Am J Alzheimers Dis Other Demen. 2018 Jun;33(4):242–246. doi: 10.1177/1533317518758785. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Ngandu T, Lehtisalo J, Solomon A, et al. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. The Lancet. 2015 Jun;385(9984):2255–2263. doi: 10.1016/S0140-6736(15)60461-5. doi. [DOI] [PubMed] [Google Scholar]
10.Ge S, Zhu Z, Wu B, McConnell ES. Technology-based cognitive training and rehabilitation interventions for individuals with mild cognitive impairment: a systematic review. BMC Geriatr. 2018 Sep 15;18(1):213. doi: 10.1186/s12877-018-0893-1. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Jandoo T. WHO guidance for digital health: what it means for researchers. Digit Health. 2020;6:2055207619898984. doi: 10.1177/2055207619898984. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Cammisuli DM, Innocenti A, Franzoni F, Pruneti C. Aerobic exercise effects upon cognition in mild cognitive impairment: a systematic review of randomized controlled trials. Arch Ital Biol. 2017 Jul 1;155(1-2):54–62. doi: 10.12871/000398292017126. doi. Medline. [DOI] [PubMed] [Google Scholar]
13.Ma B, Yang J, Wong FKY, et al. Artificial intelligence in elderly healthcare: a scoping review. Ageing Res Rev. 2023 Jan;83:101808. doi: 10.1016/j.arr.2022.101808. doi. Medline. [DOI] [PubMed] [Google Scholar]
14.Brown A, O’Connor S. Mobile health applications for people with dementia: a systematic review and synthesis of qualitative studies. Informatics for Health and Social Care. 2020 Oct 1;45(4):343–359. doi: 10.1080/17538157.2020.1728536. doi. [DOI] [PubMed] [Google Scholar]
15.Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005 Feb;8(1):19–32. doi: 10.1080/1364557032000119616. doi. [DOI] [Google Scholar]
16.Levac D, Colquhoun H, O’Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010 Sep 20;5:69. doi: 10.1186/1748-5908-5-69. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for Scoping Reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018 Oct 2;169(7):467–473. doi: 10.7326/M18-0850. doi. Medline. [DOI] [PubMed] [Google Scholar]
18.Rethlefsen ML, Kirtley S, Waffenschmidt S, et al. PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Syst Rev. 2021 Jan 26;10(1):39. doi: 10.1186/s13643-020-01542-z. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Rethlefsen M, Kirtley S, Waffenschmidt S, et al. PRISMA search reporting extension. Open Science Framework. 2019. [08-12-2025]. https://OSF.IO/YGN9W URL. Accessed.
20.Peters M, Godfrey C, Mcinerney P, Munn Z, Trico A, Khalil H. JBI Reviewer’s Manual. 2020. Chapter 11: scoping reviews. doi. ISBN.978-0-6488488-0-6 [DOI] [Google Scholar]
21.Afifi T, Collins N, Rand K, et al. Using virtual reality to improve the quality of life of older adults with cognitive impairments and their family members who live at a distance. Health Commun. 2023 Oct;38(9):1904–1915. doi: 10.1080/10410236.2022.2040170. doi. Medline. [DOI] [PubMed] [Google Scholar]
22.Stogl D, Armbruster O, Mende M, Hein B, Wang XB, Meyer P. Robot-based training for people with mild cognitive impairment. IEEE Robot Autom Lett. 2019 Apr;4(2):1916–1923. doi: 10.1109/LRA.2019.2898470. doi. [DOI] [Google Scholar]
23.Au-Yeung WTM, Liu Y, Hanna R, et al. Feasibility of deploying home-based digital technology, environmental sensors, and web-based surveys for assessing behavioral symptoms and identifying their precipitants in older adults: longitudinal, observational study. JMIR Form Res. 2024 May 8;8:e53192. doi: 10.2196/53192. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Nousia A, Pappa E, Siokas V, et al. Evaluation of the efficacy and feasibility of a telerehabilitation program using language and cognitive exercises in multi-domain amnestic mild cognitive impairment. Arch Clin Neuropsychol. 2023 Feb 18;38(2):224–235. doi: 10.1093/arclin/acac078. doi. Medline. [DOI] [PubMed] [Google Scholar]
25.Fristed E, Skirrow C, Meszaros M, et al. A remote speech‐based AI system to screen for early Alzheimer’s disease via smartphones. Alz & Dem Diag Ass & Dis Mo. 2022 Jan;14(1):e12366. doi: 10.1002/dad2.12366. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Tian M, Cai YC, Zhang J. The impact of virtual reality-based products on mild cognitive impairment senior subjects: an experimental study using multiple sources of data. Appl Sci (Basel) 2023;13(4):2372. doi: 10.3390/app13042372. doi. [DOI] [Google Scholar]
27.Matsangidou M, Solomou T, Frangoudes F, et al. Affective out-world experience via virtual reality for older adults living with mild cognitive impairments or mild dementia. Int J Environ Res Public Health. 2023 Feb 7;20(4):2919. doi: 10.3390/ijerph20042919. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Chandler MJ, Locke DE, Crook JE, et al. Comparative effectiveness of behavioral interventions on quality of life for older adults with mild cognitive impairment: a randomized clinical trial. JAMA Netw Open. 2019 May 3;2(5):e193016. doi: 10.1001/jamanetworkopen.2019.3016. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Canyazo CM, Keller G, Helou B, et al. Effectiveness of cognitive rehabilitation on mild cognitive impairment using teleneuropsychology. Dement Neuropsychol. 2023;17:e20220079. doi: 10.1590/1980-5764-DN-2022-0079. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Lee J, Kim J, Park A, et al. Efficacy of a mobile-based multidomain intervention to improve cognitive function and health-related outcomes among older Korean adults with subjective cognitive decline. Journal of Alzheimer’s Disease. 2023 Jun 13;93(4):1551–1562. doi: 10.3233/JAD-221299. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Rawtaer I, Mahendran R, Kua EH, et al. Early detection of mild cognitive impairment with in-home sensors to monitor behavior patterns in community-dwelling senior citizens in Singapore: cross-sectional feasibility study. J Med Internet Res. 2020 May 5;22(5):e16854. doi: 10.2196/16854. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Chang CH, Yeh CH, Chang CC, Lin YC. Interactive somatosensory games in rehabilitation training for older adults with mild cognitive impairment: usability study. JMIR Serious Games. 2022 Jul 14;10(3):e38465. doi: 10.2196/38465. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Arlati S, Di Santo SG, Franchini F, et al. Acceptance and usability of immersive virtual reality in older adults with objective and subjective cognitive decline. Journal of Alzheimer’s Disease. 2021 Apr 6;80(3):1025–1038. doi: 10.3233/JAD-201431. doi. [DOI] [PubMed] [Google Scholar]
34.Wu YH, Wrobel J, Cornuet M, Kerhervé H, Damnée S, Rigaud AS. Acceptance of an assistive robot in older adults: a mixed-method study of human–robot interaction over a 1-month period in the living lab setting. CIA. 2014;9:801. doi: 10.2147/CIA.S56435. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Stypulkowski K, Anquillare E, Twamley EW, Thayer RE. Feasibility of a telehealth compensatory cognitive training program for older adults with mild cognitive impairment. Clin Gerontol. 2024;47(1):17–25. doi: 10.1080/07317115.2023.2213694. doi. Medline. [DOI] [PubMed] [Google Scholar]
36.Maeng S, Hong JP, Kim WH, et al. Effects of virtual reality-based cognitive training in the elderly with and without mild cognitive impairment. Psychiatry Investig. 2021 Jul;18(7):619–627. doi: 10.30773/pi.2020.0446. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Micarelli A, Viziano A, Micarelli B, Augimeri I, Alessandrini M. Vestibular rehabilitation in older adults with and without mild cognitive impairment: effects of virtual reality using a head-mounted display. Arch Gerontol Geriatr. 2019;83:246–256. doi: 10.1016/j.archger.2019.05.008. doi. Medline. [DOI] [PubMed] [Google Scholar]
38.Li F, Harmer P, Fitzgerald K, Winters-Stone K. A cognitively enhanced online Tai Ji Quan training intervention for community-dwelling older adults with mild cognitive impairment: a feasibility trial. BMC Geriatr. 2022 Jan 25;22(1):76. doi: 10.1186/s12877-021-02747-0. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Li FZ, Harmer P, Voit J, Chou LS. Implementing an online virtual falls prevention intervention during a public health pandemic for older adults with mild cognitive impairment: a feasibility trial. CIA. 2021;Volume 16:973–983. doi: 10.2147/CIA.S306431. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Martin DM, Mohan A, Alonzo A, et al. A pilot double-blind randomized controlled trial of cognitive training combined with transcranial direct current stimulation for amnestic mild cognitive impairment. J Alzheimers Dis. 2019 Aug 12;71(2):503–512. doi: 10.3233/JAD-190306. doi. Medline. [DOI] [PubMed] [Google Scholar]
41.Hwang HF, Tseng KC, Chen SJ, Yu WY, Chen CY, Lin MR. Effects of home-based computerized cognitive training and tai chi exercise on cognitive functions in older adults with mild cognitive impairment. Aging & Mental Health. 2023 Nov 2;27(11):2170–2178. doi: 10.1080/13607863.2023.2225430. doi. [DOI] [PubMed] [Google Scholar]
42.Lin YF, Liu MF, Ho MH, et al. A pilot study of interactive-video games in people with mild cognitive impairment. Int J Environ Res Public Health. 2022 Mar 16;19(6):3536. doi: 10.3390/ijerph19063536. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Yan M, Yin H, Meng Q, et al. A virtual supermarket program for the screening of mild cognitive impairment in older adults: diagnostic accuracy study. JMIR Serious Games. 2021 Dec 3;9(4):e30919. doi: 10.2196/30919. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Yamada Y, Shinkawa K, Nemoto M, Nemoto K, Arai T. A mobile application using automatic speech analysis for classifying Alzheimer’s disease and mild cognitive impairment. Comput Speech Lang. 2023 Jun;81:101514. doi: 10.1016/j.csl.2023.101514. doi. [DOI] [Google Scholar]
45.Toth L, Hoffmann I, Gosztolya G, et al. A speech recognition-based solution for the automatic detection of mild cognitive impairment from spontaneous speech. Curr Alzheimer Res. 2018;15(2):130–138. doi: 10.2174/1567205014666171121114930. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Ter Huurne D, Ramakers I, Possemis N, et al. The accuracy of speech and linguistic analysis in early diagnostics of neurocognitive disorders in a memory clinic setting. Arch Clin Neuropsychol. 2023 Jul 25;38(5):667–676. doi: 10.1093/arclin/acac105. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Zhou Y, Han W, Yao X, Xue J, Li Z, Li Y. Developing a machine learning model for detecting depression, anxiety, and apathy in older adults with mild cognitive impairment using speech and facial expressions: a cross-sectional observational study. Int J Nurs Stud. 2023 Oct;146:104562. doi: 10.1016/j.ijnurstu.2023.104562. doi. Medline. [DOI] [PubMed] [Google Scholar]
48.Clarke N, Barrick TR, Garrard P. A comparison of connected speech tasks for detecting early Alzheimer’s disease and mild cognitive impairment using natural language processing and machine learning. Front Comput Sci. 2021 May 31;3:634360. doi: 10.3389/fcomp.2021.634360. doi. [DOI] [Google Scholar]
49.Tang F, Uchendu I, Wang F, Dodge HH, Zhou J. Scalable diagnostic screening of mild cognitive impairment using AI dialogue agent. Sci Rep. 2020 Mar 31;10(1):5732. doi: 10.1038/s41598-020-61994-0. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Eraslan Boz H, Limoncu H, Zygouris S, et al. A new tool to assess amnestic mild cognitive impairment in Turkish older adults: virtual supermarket (VSM) Aging, Neuropsychology, and Cognition. 2020 Sep 2;27(5):639–653. doi: 10.1080/13825585.2019.1663146. doi. [DOI] [PubMed] [Google Scholar]
51.Tsai CF, Chen CC, Wu EHK, et al. A machine-learning-based assessment method for early-stage neurocognitive impairment by an immersive virtual supermarket. IEEE Trans Neural Syst Rehabil Eng. 2021;29:2124–2132. doi: 10.1109/TNSRE.2021.3118918. doi. Medline. [DOI] [PubMed] [Google Scholar]
52.Zygouris S, Ntovas K, Giakoumis D, et al. A preliminary study on the feasibility of using a virtual reality cognitive training application for remote detection of mild cognitive impairment. Journal of Alzheimer’s Disease. 2017 Jan 24;56(2):619–627. doi: 10.3233/JAD-160518. doi. [DOI] [PubMed] [Google Scholar]
53.Tarnanas I, Tsolaki M, Nef T, M. Müri R, Mosimann UP. Can a novel computerized cognitive screening test provide additional information for early detection of Alzheimer’s disease? Alzheimer's & Dementia. 2014 Nov;10(6):790–798. doi: 10.1016/j.jalz.2014.01.002. doi. [DOI] [PubMed] [Google Scholar]
54.Zygouris S, Giakoumis D, Votis K, et al. Can a virtual reality cognitive training application fulfill a dual role? Using the virtual supermarket cognitive training application as a screening tool for mild cognitive impairment. J Alzheimers Dis. 2015;44(4):1333–1347. doi: 10.3233/JAD-141260. doi. Medline. [DOI] [PubMed] [Google Scholar]
55.Zygouris S, Iliadou P, Lazarou E, et al. Detection of mild cognitive impairment in an at-risk group of older adults: can a novel self-administered serious game-based screening test improve diagnostic accuracy? J Alzheimers Dis. 2020;78(1):405–412. doi: 10.3233/JAD-200880. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
56.Kim SY, Park J, Choi H, Loeser M, Ryu H, Seo K. Digital marker for early screening of mild cognitive impairment through hand and eye movement analysis in virtual reality using machine learning: first validation study. J Med Internet Res. 2023 Oct 20;25:e48093. doi: 10.2196/48093. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Karapapas C, Goumopoulos C. Mild cognitive impairment detection using machine learning models trained on data collected from serious games. Appl Sci (Basel) 2021 Sep;11(17):8184. doi: 10.3390/app11178184. doi. [DOI] [Google Scholar]
58.Rutkowski TM, Abe MS, Koculak M, Otake-Matsuura M. Classifying mild cognitive impairment from behavioral responses in emotional arousal and valence evaluation task - AI approach for early dementia biomarker in aging societies. Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:5537–5543. doi: 10.1109/EMBC44109.2020.9175805. doi. Medline. [DOI] [PubMed] [Google Scholar]
59.Wu J, Tu J, Liu Z, et al. An effective test (EOmciSS) for screening older adults with mild cognitive impairment in a community setting: development and validation study. J Med Internet Res. 2023 Jan;25:e40858. doi: 10.2196/40858. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Chan JYC, Wong A, Yiu B, et al. Electronic cognitive screen technology for screening older adults with dementia and mild cognitive impairment in a community setting: development and validation study. J Med Internet Res. 2020 Dec 18;22(12):e17332. doi: 10.2196/17332. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Kalafatis C, Modarres MH, Apostolou P, et al. Validity and cultural generalisability of a 5-minute AI-based, computerised cognitive assessment in mild cognitive impairment and Alzheimer’s dementia. Front Psychiatry. 2021;12:706695. doi: 10.3389/fpsyt.2021.706695. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Ghoraani B, Boettcher LN, Hssayeni MD, Rosenfeld A, Tolea MI, Galvin JE. Detection of mild cognitive impairment and Alzheimer’s disease using dual-task gait assessments and machine learning. Biomed Signal Process Control. 2021 Feb;64:102249. doi: 10.1016/j.bspc.2020.102249. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Boettcher LN, Hssayeni M, Rosenfeld A, Tolea MI, Galvin JE, Ghoraani B. Dual-task gait assessment and machine learning for early-detection of cognitive decline. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society; Jul 20-24, 2020; Montreal, QC, Canada. Presented at. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Ward EC, Sharma S, Burns C, Theodoros D, Russell T. Validity of conducting clinical dysphagia assessments for patients with normal to mild cognitive impairment via telerehabilitation. Dysphagia. 2012 Dec;27(4):460–472. doi: 10.1007/s00455-011-9390-9. doi. Medline. [DOI] [PubMed] [Google Scholar]
65.Ghani Z, Saha S, Jarl J, Andersson M, Berglund JS, Anderberg P. Short term economic evaluation of the digital platform “Support, Monitoring and Reminder Technology for Mild Dementia” (SMART4MD) for people with mild cognitive impairment and their informal caregivers. J Alzheimers Dis. 2022;86(4):1629–1641. doi: 10.3233/JAD-215013. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Schmitter-Edgecombe M, Brown K, Luna C, et al. Partnering a compensatory application with activity-aware prompting to improve use in individuals with amnestic mild cognitive impairment: a randomized controlled pilot clinical trial. J Alzheimers Dis. 2022;85(1):73–90. doi: 10.3233/JAD-215022. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
67.De Wit L, O’Shea D, Chandler M, et al. Physical exercise and cognitive engagement outcomes for mild neurocognitive disorder: a group-randomized pilot trial. Trials. 2018 Oct 19;19(1):573. doi: 10.1186/s13063-018-2865-3. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
68.Iliadou P, Paliokas I, Zygouris S, et al. A comparison of traditional and serious game-based digital markers of cognition in older adults with mild cognitive impairment and healthy controls. Journal of Alzheimer’s Disease. 2021 Feb 16;79(4):1747–1759. doi: 10.3233/JAD-201300. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Wu J, He Y, Liang S, et al. Computerized cognitive training enhances episodic memory by down-modulating posterior cingulate-precuneus connectivity in older persons with mild cognitive impairment: a randomized controlled trial. Am J Geriatr Psychiatry. 2023 Oct;31(10):820–832. doi: 10.1016/j.jagp.2023.04.008. doi. Medline. [DOI] [PubMed] [Google Scholar]
70.Palestra G, Pino O. Detecting emotions during a memory training assisted by a social robot for individuals with mild cognitive impairment (MCI) Multimed Tools Appl. 2020 Dec;79(47-48):35829–35844. doi: 10.1007/s11042-020-10092-4. doi. [DOI] [Google Scholar]
71.Teasdale N, Simoneau M, Hudon L, et al. Older adults with mild cognitive impairments show less driving errors after a multiple sessions simulator training program but do not exhibit long term retention. Front Hum Neurosci. 2016;10:653. doi: 10.3389/fnhum.2016.00653. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
72.Chang YL, Luo DH, Huang TR, Goh JOS, Yeh SL, Fu LC. Identifying mild cognitive impairment by using human-robot interactions. Libon D, editor. J Alzheimers Dis. 2022;85(3):1129–1142. doi: 10.3233/JAD-215015. doi. Medline. [DOI] [PubMed] [Google Scholar]
73.Pino O, Palestra G, Trevino R, De Carolis B. The humanoid robot NAO as trainer in a memory program for elderly people with mild cognitive impairment. Int J of Soc Robotics. 2020 Jan;12(1):21–33. doi: 10.1007/s12369-019-00533-y. doi. [DOI] [Google Scholar]
74.Moussavi Z, Kimura K, Lithgow B. Egocentric spatial orientation differences between Alzheimer’s disease at early stages and mild cognitive impairment: a diagnostic aid. Med Biol Eng Comput. 2022 Feb;60(2):501–509. doi: 10.1007/s11517-021-02478-9. doi. [DOI] [PubMed] [Google Scholar]
75.Boller B, Ouellet É, Belleville S. Using virtual reality to assess and promote transfer of memory training in older adults with memory complaints: a randomized controlled trial. Front Psychol. 2021;12:627242. doi: 10.3389/fpsyg.2021.627242. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
76.Hassandra M, Galanis E, Hatzigeorgiadis A, et al. Α virtual reality app for physical and cognitive training of older people with mild cognitive impairment: mixed methods feasibility study. JMIR Serious Games. 2021 Mar 24;9(1):e24170. doi: 10.2196/24170. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
77.Wild KV, Mattek NC, Maxwell SA, Dodge HH, Jimison HB, Kaye JA. Computer‐related self‐efficacy and anxiety in older adults with and without mild cognitive impairment. Alzheimer's & Dementia. 2012 Nov;8(6):544–552. doi: 10.1016/j.jalz.2011.12.008. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
78.Arshad H, Anwar K, Khattak HG, Amjad I, Majeed Y. Effect of brain training game on mild cognitive impairment (MCI) in older adults. [27-11-2025];PJMHS. 2021 Sep 30;15(9):2272–2275. doi: 10.53350/pjmhs211592272. https://pjmhsonline.com/published-issues/2021/september URL. Accessed. doi. [DOI] [Google Scholar]
79.Nousia A, Martzoukou M, Petri MC, Messinis L, Nasios G. Face-to-face vs. telerehabilitation language and cognitive training in patients with multi-domain amnestic mild cognitive impairment. Appl Neuropsychol Adult. 2025;32(5):1282–1290. doi: 10.1080/23279095.2023.2259035. doi. Medline. [DOI] [PubMed] [Google Scholar]
80.Manenti R, Gobbi E, Baglio F, et al. Effectiveness of an innovative cognitive treatment and telerehabilitation on subjects with mild cognitive impairment: a multicenter, randomized, active-controlled study. Front Aging Neurosci. 2020;12:585988. doi: 10.3389/fnagi.2020.585988. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
81.Wang Y, Chen T, Wang C, et al. A new smart 2-min mobile alerting method for mild cognitive impairment due to Alzheimer’s disease in the community. Brain Sci. 2023 Jan 31;13(2):244. doi: 10.3390/brainsci13020244. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
82.Weniger G, Ruhleder M, Lange C, Wolf S, Irle E. Egocentric and allocentric memory as assessed by virtual reality in individuals with amnestic mild cognitive impairment. Neuropsychologia. 2011 Feb;49(3):518–527. doi: 10.1016/j.neuropsychologia.2010.12.031. doi. Medline. [DOI] [PubMed] [Google Scholar]
83.Tarnanas I, Papagiannopoulos S, Kazis D, Wiederhold M, Widerhold B, Tsolaki M. Reliability of a novel serious game using dual-task gait profiles to early characterize aMCI. Front Aging Neurosci. 2015;7:50. doi: 10.3389/fnagi.2015.00050. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
84.Jirayucharoensak S, Israsena P, Pan-Ngum S, Hemrungrojn S, Maes M. A game-based neurofeedback training system to enhance cognitive performance in healthy elderly subjects and in patients with amnestic mild cognitive impairment. Clin Interv Aging. 2019;14:347–360. doi: 10.2147/CIA.S189047. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
85.Savulich G, Piercy T, Fox C, et al. Cognitive training using a novel memory game on an iPad in patients with amnestic mild cognitive impairment (aMCI) Int J Neuropsychopharmacol. 2017 Aug 1;20(8):624–633. doi: 10.1093/ijnp/pyx040. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
86.Kim H, Hong JP, Kang JM, et al. Cognitive reserve and the effects of virtual reality-based cognitive training on elderly individuals with mild cognitive impairment and normal cognition. Psychogeriatrics. 2021 Jul;21(4):552–559. doi: 10.1111/psyg.12705. doi. Medline. [DOI] [PubMed] [Google Scholar]
87.Cogné M, Auriacombe S, Vasa L, et al. Are visual cues helpful for virtual spatial navigation and spatial memory in patients with mild cognitive impairment or Alzheimer’s disease? Neuropsychology. 2018 May;32(4):385–400. doi: 10.1037/neu0000435. doi. Medline. [DOI] [PubMed] [Google Scholar]
88.Zhao Y, Li L, He X, et al. Psychodynamic-based virtual reality cognitive training system with personalized emotional arousal elements for mild cognitive impairment patients. Comput Methods Programs Biomed. 2023 Nov;241:107779. doi: 10.1016/j.cmpb.2023.107779. doi. [DOI] [PubMed] [Google Scholar]
89.Park JH, Liao Y, Kim DR, et al. Feasibility and tolerability of a culture-based virtual reality (VR) training program in patients with mild cognitive impairment: a randomized controlled pilot study. Int J Environ Res Public Health. 2020 Apr 27;17(9):3030. doi: 10.3390/ijerph17093030. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
90.Delmastro F, Martino FD, Dolciotti C. Cognitive training and stress detection in MCI frail older people through wearable sensors and machine learning. IEEE Access. 2020;8:65573–65590. doi: 10.1109/ACCESS.2020.2985301. doi. [DOI] [Google Scholar]
91.Gelonch O, Ribera M, Codern-Bové N, et al. Acceptability of a lifelogging wearable camera in older adults with mild cognitive impairment: a mixed-method study. BMC Geriatr. 2019 Apr 16;19(1):110. doi: 10.1186/s12877-019-1132-0. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
92.Locke DEC, Khayoun R, Shandera-Ochsner AL, et al. Innovation inspired by COVID: a virtual treatment program for patients with mild cognitive impairment at Mayo Clinic. Mayo Clin Proc Innov Qual Outcomes. 2021 Oct;5(5):820–826. doi: 10.1016/j.mayocpiqo.2021.06.004. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
93.Lai YL, Chen WY, Hsu LY, Fu CH. The effect of a tele-health intervention program on home-dwelling persons with dementia or MCI and on their primary caregivers during the stay-at-home-order period in the COVID-19 pandemic outbreak: evidence from Taiwan. Healthcare (Basel) 2022 May 24;10(6):969. doi: 10.3390/healthcare10060969. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
94.Finn M, McDonald S. A single case study of computerised cognitive training for older persons with mild cognitive impairment. NeuroRehabilitation. 2014 Jan 1;35(2):261–270. doi: 10.3233/NRE-141121. doi. Medline. [DOI] [PubMed] [Google Scholar]
95.Ianculescu M, Paraschiv EA, Alexandru A. Addressing mild cognitive impairment and boosting wellness for the elderly through personalized remote monitoring. Healthcare (Basel) 10(7):1214. doi: 10.3390/healthcare10071214. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
96.Lee LP, Har AWY, Ngai CH, Lai DWL, Lam BYH, Chan CCH. Audiovisual integrative training for augmenting cognitive- motor functions in older adults with mild cognitive impairment. BMC Geriatr. 2020 Feb 17;20(1):64. doi: 10.1186/s12877-020-1465-8. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
97.Cammisuli DM, Isella V, Verde F, et al. Behavioral disorders of spatial cognition in patients with mild cognitive impairment due to Alzheimer’s disease: preliminary findings from the BDSC-MCI project. J Clin Med. 13(4):1178. doi: 10.3390/jcm13041178. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
98.Nousia A, Martzoukou M, Siokas V, et al. Beneficial effect of computer-based multidomain cognitive training in patients with mild cognitive impairment. Applied Neuropsychology: Adult. 2021 Nov 2;28(6):717–726. doi: 10.1080/23279095.2019.1692842. doi. [DOI] [PubMed] [Google Scholar]
99.Luna C, Cook DJ, Schmitter-Edgecombe M. But will they use it? Predictors of adoption of an electronic memory aid in individuals with amnestic mild cognitive impairment. Neuropsychology. 37(8):955–965. doi: 10.1037/neu0000898. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
100.Park JH. Can the virtual reality-based spatial memory test better discriminate mild cognitive impairment than neuropsychological assessment? IJERPH. 19(16):9950. doi: 10.3390/ijerph19169950. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
101.Lau CI, Liu MN, Cheng FY, Wang HC, Walsh V, Liao YY. Can transcranial direct current stimulation combined with interactive computerized cognitive training boost cognition and gait performance in older adults with mild cognitive impairment? A randomized controlled trial. J Neuroeng Rehabil. 21(1) doi: 10.1186/s12984-024-01313-0. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
102.Walker G, Morris LA, Christensen H, Mirheidari B, Reuber M, Blackburn DJ. Characterising spoken responses to an intelligent virtual agent by persons with mild cognitive impairment. Clin Linguist Phon. 2021 Mar 4;35(3):237–252. doi: 10.1080/02699206.2020.1777586. doi. Medline. [DOI] [PubMed] [Google Scholar]
103.Lin F, Heffner KL, Ren P, et al. Cognitive and neural effects of vision-based speed-of-processing training in older adults with amnestic mild cognitive impairment: a pilot study. [27-11-2025];J Am Geriatr Soc. 2016 Jun;64(6):1293–1298. doi: 10.1111/jgs.14132. https://agsjournals.onlinelibrary.wiley.com/toc/15325415/64/6 URL. Accessed. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
104.Kim JH, Han JY, Park GC, Lee JS. Cognitive improvement effects of electroacupuncture combined with computer-based cognitive rehabilitation in patients with mild cognitive impairment: a randomized controlled trial. Brain Sci. 10(12):984. doi: 10.3390/brainsci10120984. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
105.Han E, Park J, Kim H, Jo G, Do HK, Lee BI. Cognitive intervention with musical stimuli using digital devices on mild cognitive impairment: a pilot study. Healthcare (Basel) 8(1):45. doi: 10.3390/healthcare8010045. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
106.Lee I, Kim D, Kim S, Kim HJ, Chung US, Lee JJ. Cognitive training based on functional near-infrared spectroscopy neurofeedback for the elderly with mild cognitive impairment: a preliminary study. Front Aging Neurosci. 15 doi: 10.3389/fnagi.2023.1168815. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
107.Hyer L, Scott C, Atkinson MM, et al. Cognitive training program to improve working memory in older adults with MCI. Clin Gerontol. 2016;39(5):410–427. doi: 10.1080/07317115.2015.1120257. doi. Medline. [DOI] [PubMed] [Google Scholar]
108.Barnes DE, Yaffe K, Belfor N, et al. Computer-based cognitive training for mild cognitive impairment. Alzheimer Disease & Associated Disorders. 2009;23(3):205–210. doi: 10.1097/WAD.0b013e31819c6137. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
109.Finn M, McDonald S. Computerised cognitive training for older persons with mild cognitive impairment: a pilot study using a randomised controlled trial design. Brain Impair. 2011 Dec 1;12(3):187–199. doi: 10.1375/brim.12.3.187. doi. [DOI] [Google Scholar]
110.Dowell-Esquivel C, Czaja SJ, Kallestrup P, Depp CA, Saber JN, Harvey PD. Computerized cognitive and skills training in older people with mild cognitive impairment: using ecological momentary assessment to index treatment-related changes in real-world performance of technology-dependent functional tasks. Am J Geriatr Psychiatry. 2024 Apr;32(4):446–459. doi: 10.1016/j.jagp.2023.10.014. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
111.Djabelkhir L, Wu YH, Vidal JS, et al. Computerized cognitive stimulation and engagement programs in older adults with mild cognitive impairment: comparing feasibility, acceptability, and cognitive and psychosocial effects. Clin Interv Aging. 2017;12:1967–1975. doi: 10.2147/CIA.S145769. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
112.Li BY, He NY, Qiao Y, et al. Computerized cognitive training for Chinese mild cognitive impairment patients: a neuropsychological and fMRI study. Neuroimage Clin. 2019;22:101691. doi: 10.1016/j.nicl.2019.101691. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
113.Duff K, Ying J, Suhrie KR, et al. Computerized cognitive training in amnestic mild cognitive impairment: a randomized clinical trial. J Geriatr Psychiatry Neurol. 2022 May;35(3):400–409. doi: 10.1177/08919887211006472. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
114.Nwosu A, Qian M, Phillips J, et al. Computerized cognitive training in mild cognitive impairment: findings in African Americans and Caucasians. J Prev Alzheimers Dis. 2024;11(1):149–154. doi: 10.14283/jpad.2023.80. doi. Medline. [DOI] [PubMed] [Google Scholar]
115.Raghunath N, Dahmen J, Brown K, Cook D, Schmitter-Edgecombe M. Creating a digital memory notebook application for individuals with mild cognitive impairment to support everyday functioning. Disability and Rehabilitation: Assistive Technology. 2020 May 18;15(4):421–431. doi: 10.1080/17483107.2019.1587017. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
116.Castilla D, Suso-Ribera C, Zaragoza I, Garcia-Palacios A, Botella C. Designing ICTs for users with mild cognitive impairment: a usability study. Int J Environ Res Public Health. 17(14):5153. doi: 10.3390/ijerph17145153. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
117.Diaz Baquero AA, Perea Bartolomé MV, Toribio-Guzmán JM, et al. Determinants of adherence to a “GRADIOR” computer-based cognitive training program in people with mild cognitive impairment (MCI) and mild dementia. J Clin Med. 11(6):1714. doi: 10.3390/jcm11061714. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]
118.Yang HL, Chu H, Kao CC, et al. Development and effectiveness of virtual interactive working memory training for older people with mild cognitive impairment: a single-blind randomised controlled trial. Age Ageing. 2019 Jul 1;48(4):519–525. doi: 10.1093/ageing/afz029. doi. Medline. [DOI] [PubMed] [Google Scholar]
119.Park JH. Does the virtual shopping training improve executive function and instrumental activities of daily living of patients with mild cognitive impairment? Asian J Psychiatr. 2022 Mar;69:102977. doi: 10.1016/j.ajp.2021.102977. doi. Medline. [DOI] [PubMed] [Google Scholar]
120.Simfukwe C, Youn YC, Kim SY, An SS. Digital trail making test-black and white: normal vs MCI. Appl Neuropsychol Adult. 2022;29(6):1296–1303. doi: 10.1080/23279095.2021.1871615. doi. Medline. [DOI] [PubMed] [Google Scholar]
121.Harvey PD, Dowell-Esquivel C, Macchiarelli JE, Martinez A, Kallestrup P, Czaja SJ. Early prediction of mastery of a computerized functional skills training program in participants with mild cognitive impairment. Int Psychogeriatr. 2024 Dec;36(12):1182–1193. doi: 10.1017/S1041610224000115. doi. Medline. [DOI] [PubMed] [Google Scholar]
122.Amjad I, Toor H, Niazi IK, et al. Xbox 360 Kinect cognitive games improve slowness, complexity of EEG, and cognitive functions in subjects with mild cognitive impairment: a randomized control trial. Games Health J. 2019 Apr;8(2):144–152. doi: 10.1089/g4h.2018.0029. doi. Medline. [DOI] [PubMed] [Google Scholar]
123.Park E, Yun BJ, Min YS, et al. Effects of a mixed reality-based cognitive training system compared to a conventional computer-assisted cognitive training system on mild cognitive impairment: a pilot study. Cogn Behav Neurol. 2019 Sep;32(3):172–178. doi: 10.1097/WNN.0000000000000197. doi. Medline. [DOI] [PubMed] [Google Scholar]
124.Kim S, Park E, Cha H, Jung JC, Jung TD, Chang Y. Effects of cognitive training in mild cognitive impairment measured by resting state functional imaging. Behav Sci (Basel) 2020 Nov 17;10(11):175. doi: 10.3390/bs10110175. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
125.Mirza RA, Yaqoob I. Effects of combined aerobic and virtual reality-based cognitive training on 76 years old diabetic male with mild cognitive impairment. J Coll Physicians Surg Pak. 2018 Sep;28(9):S210–S212. doi: 10.29271/jcpsp.2018.09.S210. doi. Medline. [DOI] [PubMed] [Google Scholar]
126.Mrakic-Sposta S, Di Santo SG, Franchini F, et al. Effects of combined physical and cognitive virtual reality-based training on cognitive impairment and oxidative stress in MCI patients: a pilot study. Front Aging Neurosci. 2018;10:282. doi: 10.3389/fnagi.2018.00282. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
127.Wu J, He Y, Liang S, et al. Effects of computerized cognitive training on structure‒function coupling and topology of multiple brain networks in people with mild cognitive impairment: a randomized controlled trial. Alzheimers Res Ther. 2023 Sep 23;15(1):158. doi: 10.1186/s13195-023-01292-9. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
128.Sato K, Ochi A, Watanabe K, Yamada K. Effects of dance video game training on cognitive functions of community-dwelling older adults with mild cognitive impairment. Aging Clin Exp Res. 2023 May;35(5):987–994. doi: 10.1007/s40520-023-02374-2. doi. Medline. [DOI] [PubMed] [Google Scholar]
129.Lim EH, Kim DS, Won YH, et al. Effects of home based serious game training (Brain Talk TM) in the elderly with mild cognitive impairment: randomized, a single-blind, controlled trial. Brain Neurorehabil. 2023 Mar;16(1):e4. doi: 10.12786/bn.2023.16.e4. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
130.Baik JS, Min JH, Ko SH, et al. Effects of home-based computerized cognitive training in community-dwelling adults with mild cognitive impairment. IEEE J Transl Eng Health Med. 2024;12:97–105. doi: 10.1109/JTEHM.2023.3317189. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
131.Park JH. Effects of spatial cognitive training using virtual reality on hippocampal functions and prefrontal cortex activity in older adults with mild cognitive impairment. [27-11-2025];Int J Gerontol. 2022 16(3):242–246. doi: 10.6890/IJGE.202207_16(3).0014. http://www.sgecm.org.tw/ijge/journal/detail.asp?id=504&title=Effects%20of%20Spatial%20Cognitive%20Training%20Using%20Virtual%20Reality%20on%20Hippocampal%20Functions%20and%20Prefrontal%20Cortex%20Activity%20in%20Older%20Adults%20with%20Mild%20Cognitive%20Impairment URL. Accessed. doi. [DOI] [Google Scholar]
132.Çinar N, Şahiner TAH. Effects of the online computerized cognitive training program BEYNEX on the cognitive tests of individuals with subjective cognitive impairment and Alzheimer’s disease on rivastigmine therapy. Turk J Med Sci. 2020 Feb 13;50(1):231–238. doi: 10.3906/sag-1905-244. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
133.Baldimtsi E, Mouzakidis C, Karathanasi EM, et al. Effects of virtual reality physical and cognitive training intervention on cognitive abilities of elders with mild cognitive impairment. J Alzheimers Dis Rep. 2023;7(1):1475–1490. doi: 10.3233/ADR-230099. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
134.Liao YY, Chen IH, Lin YJ, Chen Y, Hsu WC. Effects of virtual reality-based physical and cognitive training on executive function and dual-task gait performance in older adults with mild cognitive impairment: a randomized control trial. Front Aging Neurosci. 2019;11:162. doi: 10.3389/fnagi.2019.00162. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
135.Park JH. Effects of virtual reality-based spatial cognitive training on hippocampal function of older adults with mild cognitive impairment. Int Psychogeriatr. 2022 Feb;34(2):157–163. doi: 10.1017/S1041610220001131. doi. Medline. [DOI] [PubMed] [Google Scholar]
136.Alegret M, Espinosa A, Ortega G, et al. From face-to-face to home-to-home: validity of a teleneuropsychological battery. J Alzheimers Dis. 2021;81(4):1541–1553. doi: 10.3233/JAD-201389. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
137.Pereira-Morales AJ, Cruz-Salinas AF, Aponte J, Pereira-Manrique F. Efficacy of a computer-based cognitive training program in older people with subjective memory complaints: a randomized study. Int J Neurosci. 2018 Jan;128(1):1–9. doi: 10.1080/00207454.2017.1308930. doi. Medline. [DOI] [PubMed] [Google Scholar]
138.Ramnath U, Rauch L, Lambert EV, Kolbe-Alexander T. Efficacy of interactive video gaming in older adults with memory complaints: a cluster-randomized exercise intervention. PLoS ONE. 2021;16(5):e0252016. doi: 10.1371/journal.pone.0252016. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
139.Jones KT, Ostrand AE, Gazzaley A, Zanto TP. Enhancing cognitive control in amnestic mild cognitive impairment via at-home non-invasive neuromodulation in a randomized trial. Sci Rep. 2023 May 8;13(1):7435. doi: 10.1038/s41598-023-34582-1. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
140.Shamir D, Loubani K, Schaham NG, Buckman Z, Rand D. Experiences of older adults with mild cognitive impairment from cognitive self-training using touchscreen tablets. Games Health J. 2024 Feb;13(1):13–24. doi: 10.1089/g4h.2023.0017. doi. Medline. [DOI] [PubMed] [Google Scholar]
141.Li N, Yang X, Du W, et al. Exploratory research on key technology of human-computer interactive 2.5-minute fast digital early warning for mild cognitive impairment. Comput Intell Neurosci. 2022;2022:2495330. doi: 10.1155/2022/2495330. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
142.Goumopoulos C, Skikos G, Frounta M. Feasibility and effects of cognitive training with the COGNIPLAT game platform in elderly with mild cognitive impairment: pilot randomized controlled trial. Games Health J. 2023 Oct;12(5):414–425. doi: 10.1089/g4h.2023.0029. doi. Medline. [DOI] [PubMed] [Google Scholar]
143.Sachs BC, Latham LA, Bateman JR, et al. Feasibility of remote administration of the uniform data set-version 3 for assessment of older adults with mild cognitive impairment and Alzheimer’s disease. Arch Clin Neuropsychol. 2024 Jul 24;39(5):635–643. doi: 10.1093/arclin/acae001. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
144.Zhu K, Zhang Q, He B, Huang M, Lin R, Li H. Immersive virtual reality-based cognitive intervention for the improvement of cognitive function, depression, and perceived stress in older adults with mild cognitive impairment and mild dementia: pilot pre-post study. JMIR Serious Games. 2022 Feb 21;10(1):e32117. doi: 10.2196/32117. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
145.Harvey PD, Chirino M, Mueller A, et al. Improvements in performance based measures of functional capacity and cognition after computerized functional skills training in older people with mild cognitive impairment and healthy comparators. Psychiatry Res. 2024 Apr;334:115792. doi: 10.1016/j.psychres.2024.115792. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
146.Dodge HH, Yu K, Wu CY, et al. Internet-based conversational engagement randomized controlled clinical trial (I-CONECT) among socially isolated adults 75+ years old with normal cognition or mild cognitive impairment: topline results. Gerontologist. 2024 Apr 1;64(4):gnad147. doi: 10.1093/geront/gnad147. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
147.Damirchi A, Hosseini F, Babaei P. Mental training enhances cognitive function and BDNF more than either physical or combined training in elderly women with MCI: a small-scale study. Am J Alzheimers Dis Other Demen. 2018 Feb;33(1):20–29. doi: 10.1177/1533317517727068. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
148.Styliadis C, Kartsidis P, Paraskevopoulos E, Ioannides AA, Bamidis PD. Neuroplastic effects of combined computerized physical and cognitive training in elderly individuals at risk for dementia: an eLORETA controlled study on resting states. Neural Plast. 2015;2015:172192. doi: 10.1155/2015/172192. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
149.Oh MW, Ki YJ, Jeon BH, et al. Nurse-led computerized cognitive training for mild cognitive impairment: a preliminary study. Rehabil Nurs. 2020 Apr 15; doi: 10.1097/RNJ.0000000000000264. doi. Medline. [DOI] [PubMed] [Google Scholar]
150.Herrera C, Chambon C, Michel BF, Paban V, Alescio-Lautier B. Positive effects of computer-based cognitive training in adults with mild cognitive impairment. Neuropsychologia. 2012 Jul;50(8):1871–1881. doi: 10.1016/j.neuropsychologia.2012.04.012. doi. Medline. [DOI] [PubMed] [Google Scholar]
151.Mendoza Laiz N, Del Valle Díaz S, Rioja Collado N, Gomez-Pilar J, Hornero R. Potential benefits of a cognitive training program in mild cognitive impairment (MCI) Restor Neurol Neurosci. 2018;36(2):207–213. doi: 10.3233/RNN-170754. doi. Medline. [DOI] [PubMed] [Google Scholar]
152.Hackett K, Lehman S, Divers R, et al. Remind me to remember: a pilot study of a novel smartphone reminder application for older adults with dementia and mild cognitive impairment. Neuropsychol Rehabil. 2022 Jan;32(1):22–50. doi: 10.1080/09602011.2020.1794909. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
153.Wu R, Li A, Xue C, et al. Screening for mild cognitive impairment with speech interaction based on virtual reality and wearable devices. Brain Sci. 2023 Aug 21;13(8):1222. doi: 10.3390/brainsci13081222. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
154.Formica C, Bonanno M, Sorbera C, et al. Smartphone-based cognitive telerehabilitation: a usability and feasibility study focusing on mild cognitive impairment. Sensors (Basel) 2024 Jan 15;24(2):525. doi: 10.3390/s24020525. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
155.Liu H, Yang X, Wang X, Yang X, Zhang X, Li Q. Study on adjuvant medication for patients with mild cognitive impairment based on VR technology and health education. Contrast Media Mol Imaging. 2021;2021:1187704. doi: 10.1155/2021/1187704. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
156.Bekrater-Bodmann R, Löffler A, Silvoni S, et al. Tablet-based sensorimotor home-training system for amnestic mild cognitive impairments in the elderly: design of a randomised clinical trial. BMJ Open. 2019 Aug 2;9(8):e028632. doi: 10.1136/bmjopen-2018-028632. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
157.Wang C, Liu S, Li A, Liu J. Text dialogue analysis for primary screening of mild cognitive impairment: development and validation study. J Med Internet Res. 2023 Dec 29;25:e51501. doi: 10.2196/51501. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
158.Anderson-Hanley C, Barcelos NM, Zimmerman EA, et al. The Aerobic and Cognitive Exercise Study (ACES) for community-dwelling older adults with or at-risk for mild cognitive impairment (MCI): neuropsychological, neurobiological and neuroimaging outcomes of a randomized clinical trial. Front Aging Neurosci. 2018;10:76. doi: 10.3389/fnagi.2018.00076. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
159.Givon Schaham N, Vitek H, Donda N, Elbo Golan I, Buckman Z, Rand D. The development and feasibility of TECH: Tablet Enhancement of Cognition and Health, a novel cognitive intervention for people with mild cognitive impairment. Games Health J. 2020 Oct;9(5):346–352. doi: 10.1089/g4h.2019.0157. doi. Medline. [DOI] [PubMed] [Google Scholar]
160.Thapa N, Park HJ, Yang JG, et al. The effect of a virtual reality-based intervention program on cognition in older adults with mild cognitive impairment: a randomized control trial. J Clin Med. 2020 Apr 29;9(5):1283. doi: 10.3390/jcm9051283. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
161.Oh W, Park H, Hallett M, You JSH. The effectiveness of a multimodal brain empowerment program in mild cognitive impairment: a single-blind, quasi-randomized experimental study. J Clin Med. 2023 Jul 26;12(15):4895. doi: 10.3390/jcm12154895. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
162.Torpil B, Şahin S, Pekçetin S, Uyanık M. The effectiveness of a virtual reality-based intervention on cognitive functions in older adults with mild cognitive impairment: a single-blind, randomized controlled trial. Games Health J. 2021 Apr;10(2):109–114. doi: 10.1089/g4h.2020.0086. doi. Medline. [DOI] [PubMed] [Google Scholar]
163.Torpil B, Pekçetin E, Pekçetin S. The effectiveness of cognitive rehabilitation intervention with the telerehabilitation method for amnestic mild cognitive impairment: a feasibility randomized controlled trial. J Telemed Telecare. 2025 Apr;31(3):320–327. doi: 10.1177/1357633X231189541. doi. Medline. [DOI] [PubMed] [Google Scholar]
164.González-Palau F, Franco M, Bamidis P, et al. The effects of a computer-based cognitive and physical training program in a healthy and mildly cognitive impaired aging sample. Aging Ment Health. 2014 Sep;18(7):838–846. doi: 10.1080/13607863.2014.899972. doi. Medline. [DOI] [PubMed] [Google Scholar]
165.Choi W, Lee S. The effects of virtual kayak paddling exercise on postural balance, muscle performance, and cognitive function in older adults with mild cognitive impairment: a randomized controlled trial. J Aging Phys Act. 2019 Dec 1;27(4):861–870. doi: 10.1123/japa.2018-0020. doi. Medline. [DOI] [PubMed] [Google Scholar]
166.Lai CH, Pai MC. The feasibility and practicality of auxiliary detection of spatial navigation impairment in patients with mild cognitive impairment due to Alzheimer’s disease by using virtual reality. Heliyon. 2024 Feb 15;10(3):e24748. doi: 10.1016/j.heliyon.2024.e24748. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
167.Park EA, Jung AR, Lee KA. The humanoid robot Sil-Bot in a cognitive training program for community-dwelling elderly people with mild cognitive impairment during the COVID-19 pandemic: a randomized controlled trial. Int J Environ Res Public Health. 2021 Aug 3;18(15):8198. doi: 10.3390/ijerph18158198. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
168.Manca M, Paternò F, Santoro C, et al. The impact of serious games with humanoid robots on mild cognitive impairment older adults. Int J Hum Comput Stud. 2021 Jan;145:102509. doi: 10.1016/j.ijhcs.2020.102509. doi. [DOI] [Google Scholar]
169.Cabinio M, Rossetto F, Isernia S, et al. The use of a virtual reality platform for the assessment of the memory decline and the hippocampal neural injury in subjects with mild cognitive impairment: the validity of Smart Aging Serious Game (SASG) J Clin Med. 2020 May 6;9(5):1355. doi: 10.3390/jcm9051355. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
170.Sheehy L, Sveistrup H, Knoefel F, et al. The use of home-based nonimmersive virtual reality to encourage physical and cognitive exercise in people with mild cognitive impairment: a feasibility study. J Aging Phys Act. 2022 Apr 1;30(2):297–307. doi: 10.1123/japa.2021-0043. doi. Medline. [DOI] [PubMed] [Google Scholar]
171.Vermeij A, Claassen J, Dautzenberg PLJ, Kessels RPC. Transfer and maintenance effects of online working-memory training in normal ageing and mild cognitive impairment. Neuropsychol Rehabil. 2016 Oct;26(5-6):783–809. doi: 10.1080/09602011.2015.1048694. doi. Medline. [DOI] [PubMed] [Google Scholar]
172.Li A, Xue C, Wu R, Wu W, Zhao J, Qiang Y. Unearthing subtle cognitive variations: a digital screening tool for detecting and monitoring mild cognitive impairment. International Journal of Human–Computer Interaction. 2025 Feb 16;41(4):2579–2599. doi: 10.1080/10447318.2024.2327179. doi. [DOI] [Google Scholar]
173.Tuena C, Serino S, Stramba-Badiale C, et al. Usability of an embodied CAVE system for spatial navigation training in mild cognitive impairment. J Clin Med. 2023 Mar 1;12(5):1949. doi: 10.3390/jcm12051949. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
174.Bourrelier J, Ryard J, Dion M, Merienne F, Manckoundia P, Mourey F. Use of a virtual environment to engage motor and postural abilities in elderly subjects with and without mild cognitive impairment (MAAMI Project) IRBM. 2016 Apr;37(2):75–80. doi: 10.1016/j.irbm.2016.02.007. doi. [DOI] [Google Scholar]
175.Werner P, Rabinowitz S, Klinger E, Korczyn AD, Josman N. Use of the virtual action planning supermarket for the diagnosis of mild cognitive impairment: a preliminary study. Dement Geriatr Cogn Disord. 2009;27(4):301–309. doi: 10.1159/000204915. doi. Medline. [DOI] [PubMed] [Google Scholar]
176.Mondellini M, Arlati S, Gapeyeva H, et al. User experience during an immersive virtual reality-based cognitive task: a comparison between Estonian and Italian older adults with MCI. Sensors (Basel) 2022 Oct 27;22(21):8249. doi: 10.3390/s22218249. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
177.Plancher G, Tirard A, Gyselinck V, Nicolas S, Piolino P. Using virtual reality to characterize episodic memory profiles in amnestic mild cognitive impairment and Alzheimer’s disease: influence of active and passive encoding. Neuropsychologia. 2012 Apr;50(5):592–602. doi: 10.1016/j.neuropsychologia.2011.12.013. doi. Medline. [DOI] [PubMed] [Google Scholar]
178.Mohammadi A, Kargar M, Hesami E. Using virtual reality to distinguish subjects with multiple- but not single-domain amnestic mild cognitive impairment from normal elderly subjects. Psychogeriatrics. 2018 Mar;18(2):132–142. doi: 10.1111/psyg.12301. doi. Medline. [DOI] [PubMed] [Google Scholar]
179.Liao YY, Tseng HY, Lin YJ, Wang CJ, Hsu WC. Using virtual reality-based training to improve cognitive function, instrumental activities of daily living and neural efficiency in older adults with mild cognitive impairment. Eur J Phys Rehabil Med. 2020 Feb;56(1):47–57. doi: 10.23736/S1973-9087.19.05899-4. doi. Medline. [DOI] [PubMed] [Google Scholar]
180.Skirrow C, Meszaros M, Meepegama U, et al. Validation of a remote and fully automated story recall task to assess for early cognitive impairment in older adults: longitudinal case-control observational study. JMIR Aging. 2022 Sep 30;5(3):e37090. doi: 10.2196/37090. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
181.Cerino ES, Katz MJ, Wang C, et al. Variability in cognitive performance on mobile devices is sensitive to mild cognitive impairment: results from the Einstein Aging Study. Front Digit Health. 2021;3:758031. doi: 10.3389/fdgth.2021.758031. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
182.Seo K, Kim JK, Oh DH, Ryu H, Choi H. Virtual daily living test to screen for mild cognitive impairment using kinematic movement analysis. PLoS ONE. 2017;12(7):e0181883. doi: 10.1371/journal.pone.0181883. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
183.Yang JG, Thapa N, Park HJ, et al. Virtual reality and exercise training enhance brain, cognitive, and physical health in older adults with mild cognitive impairment. Int J Environ Res Public Health. 2022 Oct 15;19(20):13300. doi: 10.3390/ijerph192013300. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
184.Park JS, Jung YJ, Lee G. Virtual reality-based cognitive-motor rehabilitation in older adults with mild cognitive impairment: a randomized controlled study on motivation and cognitive function. Healthcare (Basel) 2020 Sep 11;8(3):335. doi: 10.3390/healthcare8030335. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
185.Jang S, Choi SW, Son SJ, et al. Virtual reality-based monitoring test for MCI: a multicenter feasibility study. Front Psychiatry. 2022;13:1057513. doi: 10.3389/fpsyt.2022.1057513. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
186.Formica C, Giambò FM, Latella D, et al. Humanoid robots for psychological assessment in mild cognitive impairment: from evaluation to the future of AI-driven data prediction systems. Front Psychol. 2025;16:1579626. doi: 10.3389/fpsyg.2025.1579626. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
187.Fu Y, Wang H. Clinical observation of VR virtual reality rehabilitation training combined with acupuncture in the treatment of mild cognitive impairment. SLAS Technol. 2025 Apr;31:100250. doi: 10.1016/j.slast.2025.100250. doi. Medline. [DOI] [PubMed] [Google Scholar]
188.Jones CD, Wasilko R, Zhang G, et al. Detecting sleep/wake rhythm disruption related to cognition in older adults with and without mild cognitive impairment using the myRhythmWatch platform: feasibility and correlation study. JMIR Aging. 2025 Apr 7;8:e67294. doi: 10.2196/67294. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
189.Carvalho CM, Poltronieri BC, Reuwsaat K, Reis MEA, Panizzutti R. Digital cognitive training for functionality in mild cognitive impairment: a randomized controlled clinical trial. Geroscience. 2025 Jun;47(3):5111–5121. doi: 10.1007/s11357-024-01464-x. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
190.Lin LC, Liao JY, Huang CM, et al. Effectiveness of robot-assisted board games on cognitive function and mental health for older adults with mild cognitive impairment: a cluster randomized trial. Games Health J. 2025 Aug;14(4):321–331. doi: 10.1089/g4h.2024.0207. doi. Medline. [DOI] [PubMed] [Google Scholar]
191.Buele J, Avilés-Castillo F, Del-Valle-Soto C, Varela-Aldás J, Palacios-Navarro G. Effects of a dual intervention (motor and virtual reality-based cognitive) on cognition in patients with mild cognitive impairment: a single-blind, randomized controlled trial. J Neuroeng Rehabil. 2024 Aug 1;21(1):130. doi: 10.1186/s12984-024-01422-w. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
192.Zhu D, Al Mahmud A, Liu W. Effects of a mobile storytelling app (Huiyou) on social participation among people with mild cognitive impairment: pilot randomized controlled trial. JMIR Hum Factors. 2025 Jun 18;12:e70177. doi: 10.2196/70177. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
193.von Bosse A, Thum A, Mahler S, Schulz H, Weuthen P, Kunze C. Evaluating the feasibility of a dyadic, touch-based multimedia tablet intervention and its effects on the caregiver-patient relationship among individuals with mild cognitive impairment: qualitative triangulation study. JMIR Aging. 2025 Aug 28;8:e75189. doi: 10.2196/75189. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
194.Chen X, Jiang D, Ning H, et al. The experience of and needs for exergames in older adults with mild cognitive impairment: qualitative interview study. JMIR Serious Games. 2025 Jun 17;13:e53631. doi: 10.2196/53631. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
195.Ip WK, Soar J, Fong K, Wang SY, James C. An exploratory study on virtual reality technology for fall prevention in older adults with mild cognitive impairment. Sensors (Basel) 2025 May 15;25(10):3123. doi: 10.3390/s25103123. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
196.Zhang S, Wu M, Sun R, et al. Exploring the discontinuous usage behavior of digital cognitive training among older adults with mild cognitive impairment and their family members: qualitative study using the extended model of IT continuance. J Med Internet Res. 2025 Mar 25;27:e66393. doi: 10.2196/66393. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
197.Kang JM, Kim N, Yun SK, et al. Exploring transfer effects on memory and its neural mechanisms through a computerized cognitive training in mild cognitive impairment: randomized controlled trial. Psychogeriatrics. 2024 Sep;24(5):1075–1086. doi: 10.1111/psyg.13161. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
198.Demiris G, Harrison S, Sefcik J, Skubic M, Richmond TS, Hodgson NA. Feasibility and acceptability of a technology-mediated fall risk prevention intervention for older adults with mild cognitive impairment. J Gerontol A Biol Sci Med Sci. 2025 May 5;80(6):glaf043. doi: 10.1093/gerona/glaf043. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
199.Petri MC, Messinis L, Patrikelis P, et al. Feasibility and clinical effectiveness of computer-based cognitive rehabilitation in illiterate and low-educated individuals with mild cognitive impairment: preliminary data. Arch Clin Neuropsychol. 2025 Apr 27;40(3):382–393. doi: 10.1093/arclin/acae078. doi. Medline. [DOI] [PubMed] [Google Scholar]
200.Latella D, Formica C, Ielo A, et al. A feasibility and usability study of a virtual reality tool (VESPA 2.0) for cognitive rehabilitation in patients with mild cognitive impairment: an ecological approach. Front Psychol. 2024;15:1402894. doi: 10.3389/fpsyg.2024.1402894. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
201.Murata N, Nishii S, Usuha R, et al. A gamified N-back app for identifying mild-cognitive impairment in older adults. JMA J. 2025 Jan 15;8(1):174–182. doi: 10.31662/jmaj.2024-0217. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
202.Van Assche M, Petrovic M, Cambier D, et al. Socially assistive robots in aged care: expectations of older adults with MCI in assisted living facilities and their caregivers. Int J of Soc Robotics. 2024 Apr;16(4):687–698. doi: 10.1007/s12369-024-01115-3. doi. [DOI] [Google Scholar]
203.Graessel E, Jank M, Scheerbaum P, Scheuermann JS, Pendergrass A. Individualised computerised cognitive training (iCCT) for community-dwelling people with mild cognitive impairment (MCI): results on cognition in the 6-month intervention period of a randomised controlled trial (MCI-CCT study) BMC Med. 2024 Oct 15;22(1):472. doi: 10.1186/s12916-024-03647-x. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
204.Dumurgier J, Paquet C, Hugon J, et al. MemScreen: a smartphone application for detection of mild cognitive impairment: a validation study: smartphone app for MCI detection. J Prev Alzheimers Dis. 2025 Mar;12(3):100077. doi: 10.1016/j.tjpad.2025.100077. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
205.McGarry A, Roesler O, Liscombe J, et al. Much more than the malady: the promise of a web-based digital platform incorporating self-report for research and clinical care in mild cognitive impairment. Mayo Clin Proc Digit Health. 2025 Jun;3(2):100224. doi: 10.1016/j.mcpdig.2025.100224. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
206.Choi Y, Lim JS, Choi H, et al. Narrative mobile video game-based cognitive training to enhance frontal function in patients with mild cognitive impairment. Sci Rep. 2025 Jan 2;15(1):195. doi: 10.1038/s41598-024-84086-9. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
207.Chang CH, Huang KY, Kuo LH, et al. Pilot randomized controlled study on the effectiveness of a virtual reality-based dementia prevention program using self-regulated learning strategies among older adults with mild cognitive impairment. Healthcare (Basel) 2025 May 7;13(9):1082. doi: 10.3390/healthcare13091082. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
208.Ferizaj D, Stamm O, Perotti L, et al. Preliminary effects of mobile computerized cognitive training in adults with mild cognitive impairment: interim analysis of a randomized controlled trial. BMC Psychol. 2025 Mar 5;13(1):202. doi: 10.1186/s40359-025-02458-w. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
209.Butler PM, Yang J, Brown R, et al. Smartwatch- and smartphone-based remote assessment of brain health and detection of mild cognitive impairment. Nat Med. 2025 Mar;31(3):829–839. doi: 10.1038/s41591-024-03475-9. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
210.Ruzi R, Pan Y, Ng ML, et al. A speech-based mobile screening tool for mild cognitive impairment: technical performance and user engagement evaluation. Bioengineering (Basel) 2025 Jan 24;12(2):108. doi: 10.3390/bioengineering12020108. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
211.Jornkokgoud K, Makmee P, Wongupparaj P, Grecucci A. Tablet- and group-based multicomponent cognitive stimulation for older adults with mild cognitive impairment: single-group pilot study and protocol for randomized controlled trial. JMIR Res Protoc. 2025 Feb 21;14:e64465. doi: 10.2196/64465. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
212.Ip WK, Soar J, James C, Wang SY, Fong KNK. Virtual reality game-based training for preventing falls among community-dwelling older adults with mild cognitive impairment: a pilot randomized control trial study. Virtual Real. 29(1) doi: 10.1007/s10055-024-01084-y. doi. [DOI] [Google Scholar]
213.Makmee P, Wongupparaj P. VR cognitive-based intervention for enhancing cognitive functions and well-being in older adults with mild cognitive impairment: behavioral and EEG evidence. Psychosoc Interv. 2025 Jan;34(1):37–51. doi: 10.5093/pi2025a4. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
214.Beentjes KM, Neal DP, Kerkhof YJF, et al. Impact of the FindMyApps program on people with mild cognitive impairment or dementia and their caregivers; an exploratory pilot randomised controlled trial. Disabil Rehabil Assist Technol. 2023 Apr;18(3):253–265. doi: 10.1080/17483107.2020.1842918. doi. Medline. [DOI] [PubMed] [Google Scholar]
215.Seelye AM, Wild KV, Larimer N, Maxwell S, Kearns P, Kaye JA. Reactions to a remote-controlled video-communication robot in seniors’ homes: a pilot study of feasibility and acceptance. Telemed J E Health. 2012 Dec;18(10):755–759. doi: 10.1089/tmj.2012.0026. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
216.The difference between screening and diagnostic tests. UCLA Health. Aug 19, 2022. [02-08-2024]. https://www.uclahealth.org/news/article/the-difference-between-screening-and-diagnostic-tests URL. Accessed.
217.Wübker A, Zwakhalen SMG, Challis D, et al. Costs of care for people with dementia just before and after nursing home placement: primary data from eight European countries. Eur J Health Econ. 2015 Sep;16(7):689–707. doi: 10.1007/s10198-014-0620-6. doi. Medline. [DOI] [PubMed] [Google Scholar]
218.Roberto KA, McCann BR, Savla J, Blieszner R. Family caregivers’ management of behavioral expressions of dementia. Gerontologist. 2024 Jun 1;64(6):gnae020. doi: 10.1093/geront/gnae020. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
219.Fisher GG, Franks MM, Plassman BL, et al. Caring for individuals with dementia and cognitive impairment, not dementia: findings from the aging, demographics, and memory study. J Am Geriatr Soc. 2011 Mar;59(3):488–494. doi: 10.1111/j.1532-5415.2010.03304.x. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]
220.Winblad B, Amouyel P, Andrieu S, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol. 2016 Apr;15(5):455–532. doi: 10.1016/S1474-4422(16)00062-4. doi. [DOI] [PubMed] [Google Scholar]
221.Lindeza P, Rodrigues M, Costa J, Guerreiro M, Rosa MM. Impact of dementia on informal care: a systematic review of family caregivers’ perceptions. BMJ Support Palliat Care. 2024 May;14(e1):e38–e49. doi: 10.1136/bmjspcare-2020-002242. doi. [DOI] [PubMed] [Google Scholar]
222.Petersen RC, Lopez O, Armstrong MJ, et al. Practice guideline update summary: mild cognitive impairment [RETIRED]: report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology (ECronicon) 2018 Jan 16;90(3):126–135. doi: 10.1212/WNL.0000000000004826. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Multimedia Appendix 1. Search strategies.

jmir-v27-e82881-s001.xlsx^{(44.6KB, xlsx)}

DOI: 10.2196/82881

Checklist 1. PRISMA-ScR checklist.

jmir-v27-e82881-s002.docx^{(57.4KB, docx)}

DOI: 10.2196/82881

Checklist 2. PRISMA-S checklist.

jmir-v27-e82881-s003.docx^{(16.8KB, docx)}

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[R1] 1.Dementia. World Health Organization. [31-09-2025]. https://www.who.int/news-room/fact-sheets/detail/dementia URL. Accessed.

[R2] 2.Cummings JL, Tong G, Ballard C. Treatment combinations for Alzheimer’s disease: current and future pharmacotherapy options. J Alzheimers Dis. 2019;67(3):779–794. doi: 10.3233/JAD-180766. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] 3.Alzheimer’s disease facts and figures: special report 2022. Alzheimer’s Association. 2022. [31-09-2025]. https://www.alz.org/media/Documents/alzheimers-facts-and-figures-special-report-2022.pdf URL. Accessed.

[R4] 4.Jack CR, Andrews JS, Beach TG, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association workgroup. [27-11-2025];Alzheimer’s & Dementia. 2024 Aug;20(8):5143–5169. doi: 10.1002/alz.13859. https://alz-journals.onlinelibrary.wiley.com/toc/15525279/20/8 URL. Accessed. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] 5.Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med. 2004 Sep;256(3):183–194. doi: 10.1111/j.1365-2796.2004.01388.x. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R6] 6.Mitchell AJ, Beaumont H, Ferguson D, Yadegarfar M, Stubbs B. Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta-analysis. Acta Psychiatr Scand. 2014 Dec;130(6):439–451. doi: 10.1111/acps.12336. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R7] 7.Jia L, Quan M, Fu Y, et al. Dementia in China: epidemiology, clinical management, and research advances. Lancet Neurol. 2020 Jan;19(1):81–92. doi: 10.1016/S1474-4422(19)30290-X. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R8] 8.Thoits T, Dutkiewicz A, Raguckas S, et al. Association between dementia severity and recommended lifestyle changes: a retrospective cohort study. Am J Alzheimers Dis Other Demen. 2018 Jun;33(4):242–246. doi: 10.1177/1533317518758785. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] 9.Ngandu T, Lehtisalo J, Solomon A, et al. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. The Lancet. 2015 Jun;385(9984):2255–2263. doi: 10.1016/S0140-6736(15)60461-5. doi. [DOI] [PubMed] [Google Scholar]

[R10] 10.Ge S, Zhu Z, Wu B, McConnell ES. Technology-based cognitive training and rehabilitation interventions for individuals with mild cognitive impairment: a systematic review. BMC Geriatr. 2018 Sep 15;18(1):213. doi: 10.1186/s12877-018-0893-1. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] 11.Jandoo T. WHO guidance for digital health: what it means for researchers. Digit Health. 2020;6:2055207619898984. doi: 10.1177/2055207619898984. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Cammisuli DM, Innocenti A, Franzoni F, Pruneti C. Aerobic exercise effects upon cognition in mild cognitive impairment: a systematic review of randomized controlled trials. Arch Ital Biol. 2017 Jul 1;155(1-2):54–62. doi: 10.12871/000398292017126. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R13] 13.Ma B, Yang J, Wong FKY, et al. Artificial intelligence in elderly healthcare: a scoping review. Ageing Res Rev. 2023 Jan;83:101808. doi: 10.1016/j.arr.2022.101808. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R14] 14.Brown A, O’Connor S. Mobile health applications for people with dementia: a systematic review and synthesis of qualitative studies. Informatics for Health and Social Care. 2020 Oct 1;45(4):343–359. doi: 10.1080/17538157.2020.1728536. doi. [DOI] [PubMed] [Google Scholar]

[R15] 15.Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005 Feb;8(1):19–32. doi: 10.1080/1364557032000119616. doi. [DOI] [Google Scholar]

[R16] 16.Levac D, Colquhoun H, O’Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010 Sep 20;5:69. doi: 10.1186/1748-5908-5-69. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] 17.Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for Scoping Reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018 Oct 2;169(7):467–473. doi: 10.7326/M18-0850. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R18] 18.Rethlefsen ML, Kirtley S, Waffenschmidt S, et al. PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Syst Rev. 2021 Jan 26;10(1):39. doi: 10.1186/s13643-020-01542-z. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R19] 19.Rethlefsen M, Kirtley S, Waffenschmidt S, et al. PRISMA search reporting extension. Open Science Framework. 2019. [08-12-2025]. https://OSF.IO/YGN9W URL. Accessed.

[R20] 20.Peters M, Godfrey C, Mcinerney P, Munn Z, Trico A, Khalil H. JBI Reviewer’s Manual. 2020. Chapter 11: scoping reviews. doi. ISBN.978-0-6488488-0-6 [DOI] [Google Scholar]

[R21] 21.Afifi T, Collins N, Rand K, et al. Using virtual reality to improve the quality of life of older adults with cognitive impairments and their family members who live at a distance. Health Commun. 2023 Oct;38(9):1904–1915. doi: 10.1080/10410236.2022.2040170. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R22] 22.Stogl D, Armbruster O, Mende M, Hein B, Wang XB, Meyer P. Robot-based training for people with mild cognitive impairment. IEEE Robot Autom Lett. 2019 Apr;4(2):1916–1923. doi: 10.1109/LRA.2019.2898470. doi. [DOI] [Google Scholar]

[R23] 23.Au-Yeung WTM, Liu Y, Hanna R, et al. Feasibility of deploying home-based digital technology, environmental sensors, and web-based surveys for assessing behavioral symptoms and identifying their precipitants in older adults: longitudinal, observational study. JMIR Form Res. 2024 May 8;8:e53192. doi: 10.2196/53192. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] 24.Nousia A, Pappa E, Siokas V, et al. Evaluation of the efficacy and feasibility of a telerehabilitation program using language and cognitive exercises in multi-domain amnestic mild cognitive impairment. Arch Clin Neuropsychol. 2023 Feb 18;38(2):224–235. doi: 10.1093/arclin/acac078. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R25] 25.Fristed E, Skirrow C, Meszaros M, et al. A remote speech‐based AI system to screen for early Alzheimer’s disease via smartphones. Alz & Dem Diag Ass & Dis Mo. 2022 Jan;14(1):e12366. doi: 10.1002/dad2.12366. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R26] 26.Tian M, Cai YC, Zhang J. The impact of virtual reality-based products on mild cognitive impairment senior subjects: an experimental study using multiple sources of data. Appl Sci (Basel) 2023;13(4):2372. doi: 10.3390/app13042372. doi. [DOI] [Google Scholar]

[R27] 27.Matsangidou M, Solomou T, Frangoudes F, et al. Affective out-world experience via virtual reality for older adults living with mild cognitive impairments or mild dementia. Int J Environ Res Public Health. 2023 Feb 7;20(4):2919. doi: 10.3390/ijerph20042919. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] 28.Chandler MJ, Locke DE, Crook JE, et al. Comparative effectiveness of behavioral interventions on quality of life for older adults with mild cognitive impairment: a randomized clinical trial. JAMA Netw Open. 2019 May 3;2(5):e193016. doi: 10.1001/jamanetworkopen.2019.3016. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] 29.Canyazo CM, Keller G, Helou B, et al. Effectiveness of cognitive rehabilitation on mild cognitive impairment using teleneuropsychology. Dement Neuropsychol. 2023;17:e20220079. doi: 10.1590/1980-5764-DN-2022-0079. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R30] 30.Lee J, Kim J, Park A, et al. Efficacy of a mobile-based multidomain intervention to improve cognitive function and health-related outcomes among older Korean adults with subjective cognitive decline. Journal of Alzheimer’s Disease. 2023 Jun 13;93(4):1551–1562. doi: 10.3233/JAD-221299. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R31] 31.Rawtaer I, Mahendran R, Kua EH, et al. Early detection of mild cognitive impairment with in-home sensors to monitor behavior patterns in community-dwelling senior citizens in Singapore: cross-sectional feasibility study. J Med Internet Res. 2020 May 5;22(5):e16854. doi: 10.2196/16854. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R32] 32.Chang CH, Yeh CH, Chang CC, Lin YC. Interactive somatosensory games in rehabilitation training for older adults with mild cognitive impairment: usability study. JMIR Serious Games. 2022 Jul 14;10(3):e38465. doi: 10.2196/38465. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R33] 33.Arlati S, Di Santo SG, Franchini F, et al. Acceptance and usability of immersive virtual reality in older adults with objective and subjective cognitive decline. Journal of Alzheimer’s Disease. 2021 Apr 6;80(3):1025–1038. doi: 10.3233/JAD-201431. doi. [DOI] [PubMed] [Google Scholar]

[R34] 34.Wu YH, Wrobel J, Cornuet M, Kerhervé H, Damnée S, Rigaud AS. Acceptance of an assistive robot in older adults: a mixed-method study of human–robot interaction over a 1-month period in the living lab setting. CIA. 2014;9:801. doi: 10.2147/CIA.S56435. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] 35.Stypulkowski K, Anquillare E, Twamley EW, Thayer RE. Feasibility of a telehealth compensatory cognitive training program for older adults with mild cognitive impairment. Clin Gerontol. 2024;47(1):17–25. doi: 10.1080/07317115.2023.2213694. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R36] 36.Maeng S, Hong JP, Kim WH, et al. Effects of virtual reality-based cognitive training in the elderly with and without mild cognitive impairment. Psychiatry Investig. 2021 Jul;18(7):619–627. doi: 10.30773/pi.2020.0446. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] 37.Micarelli A, Viziano A, Micarelli B, Augimeri I, Alessandrini M. Vestibular rehabilitation in older adults with and without mild cognitive impairment: effects of virtual reality using a head-mounted display. Arch Gerontol Geriatr. 2019;83:246–256. doi: 10.1016/j.archger.2019.05.008. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R38] 38.Li F, Harmer P, Fitzgerald K, Winters-Stone K. A cognitively enhanced online Tai Ji Quan training intervention for community-dwelling older adults with mild cognitive impairment: a feasibility trial. BMC Geriatr. 2022 Jan 25;22(1):76. doi: 10.1186/s12877-021-02747-0. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R39] 39.Li FZ, Harmer P, Voit J, Chou LS. Implementing an online virtual falls prevention intervention during a public health pandemic for older adults with mild cognitive impairment: a feasibility trial. CIA. 2021;Volume 16:973–983. doi: 10.2147/CIA.S306431. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R40] 40.Martin DM, Mohan A, Alonzo A, et al. A pilot double-blind randomized controlled trial of cognitive training combined with transcranial direct current stimulation for amnestic mild cognitive impairment. J Alzheimers Dis. 2019 Aug 12;71(2):503–512. doi: 10.3233/JAD-190306. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R41] 41.Hwang HF, Tseng KC, Chen SJ, Yu WY, Chen CY, Lin MR. Effects of home-based computerized cognitive training and tai chi exercise on cognitive functions in older adults with mild cognitive impairment. Aging & Mental Health. 2023 Nov 2;27(11):2170–2178. doi: 10.1080/13607863.2023.2225430. doi. [DOI] [PubMed] [Google Scholar]

[R42] 42.Lin YF, Liu MF, Ho MH, et al. A pilot study of interactive-video games in people with mild cognitive impairment. Int J Environ Res Public Health. 2022 Mar 16;19(6):3536. doi: 10.3390/ijerph19063536. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R43] 43.Yan M, Yin H, Meng Q, et al. A virtual supermarket program for the screening of mild cognitive impairment in older adults: diagnostic accuracy study. JMIR Serious Games. 2021 Dec 3;9(4):e30919. doi: 10.2196/30919. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R44] 44.Yamada Y, Shinkawa K, Nemoto M, Nemoto K, Arai T. A mobile application using automatic speech analysis for classifying Alzheimer’s disease and mild cognitive impairment. Comput Speech Lang. 2023 Jun;81:101514. doi: 10.1016/j.csl.2023.101514. doi. [DOI] [Google Scholar]

[R45] 45.Toth L, Hoffmann I, Gosztolya G, et al. A speech recognition-based solution for the automatic detection of mild cognitive impairment from spontaneous speech. Curr Alzheimer Res. 2018;15(2):130–138. doi: 10.2174/1567205014666171121114930. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R46] 46.Ter Huurne D, Ramakers I, Possemis N, et al. The accuracy of speech and linguistic analysis in early diagnostics of neurocognitive disorders in a memory clinic setting. Arch Clin Neuropsychol. 2023 Jul 25;38(5):667–676. doi: 10.1093/arclin/acac105. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R47] 47.Zhou Y, Han W, Yao X, Xue J, Li Z, Li Y. Developing a machine learning model for detecting depression, anxiety, and apathy in older adults with mild cognitive impairment using speech and facial expressions: a cross-sectional observational study. Int J Nurs Stud. 2023 Oct;146:104562. doi: 10.1016/j.ijnurstu.2023.104562. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R48] 48.Clarke N, Barrick TR, Garrard P. A comparison of connected speech tasks for detecting early Alzheimer’s disease and mild cognitive impairment using natural language processing and machine learning. Front Comput Sci. 2021 May 31;3:634360. doi: 10.3389/fcomp.2021.634360. doi. [DOI] [Google Scholar]

[R49] 49.Tang F, Uchendu I, Wang F, Dodge HH, Zhou J. Scalable diagnostic screening of mild cognitive impairment using AI dialogue agent. Sci Rep. 2020 Mar 31;10(1):5732. doi: 10.1038/s41598-020-61994-0. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R50] 50.Eraslan Boz H, Limoncu H, Zygouris S, et al. A new tool to assess amnestic mild cognitive impairment in Turkish older adults: virtual supermarket (VSM) Aging, Neuropsychology, and Cognition. 2020 Sep 2;27(5):639–653. doi: 10.1080/13825585.2019.1663146. doi. [DOI] [PubMed] [Google Scholar]

[R51] 51.Tsai CF, Chen CC, Wu EHK, et al. A machine-learning-based assessment method for early-stage neurocognitive impairment by an immersive virtual supermarket. IEEE Trans Neural Syst Rehabil Eng. 2021;29:2124–2132. doi: 10.1109/TNSRE.2021.3118918. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R52] 52.Zygouris S, Ntovas K, Giakoumis D, et al. A preliminary study on the feasibility of using a virtual reality cognitive training application for remote detection of mild cognitive impairment. Journal of Alzheimer’s Disease. 2017 Jan 24;56(2):619–627. doi: 10.3233/JAD-160518. doi. [DOI] [PubMed] [Google Scholar]

[R53] 53.Tarnanas I, Tsolaki M, Nef T, M. Müri R, Mosimann UP. Can a novel computerized cognitive screening test provide additional information for early detection of Alzheimer’s disease? Alzheimer's & Dementia. 2014 Nov;10(6):790–798. doi: 10.1016/j.jalz.2014.01.002. doi. [DOI] [PubMed] [Google Scholar]

[R54] 54.Zygouris S, Giakoumis D, Votis K, et al. Can a virtual reality cognitive training application fulfill a dual role? Using the virtual supermarket cognitive training application as a screening tool for mild cognitive impairment. J Alzheimers Dis. 2015;44(4):1333–1347. doi: 10.3233/JAD-141260. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R55] 55.Zygouris S, Iliadou P, Lazarou E, et al. Detection of mild cognitive impairment in an at-risk group of older adults: can a novel self-administered serious game-based screening test improve diagnostic accuracy? J Alzheimers Dis. 2020;78(1):405–412. doi: 10.3233/JAD-200880. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R56] 56.Kim SY, Park J, Choi H, Loeser M, Ryu H, Seo K. Digital marker for early screening of mild cognitive impairment through hand and eye movement analysis in virtual reality using machine learning: first validation study. J Med Internet Res. 2023 Oct 20;25:e48093. doi: 10.2196/48093. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R57] 57.Karapapas C, Goumopoulos C. Mild cognitive impairment detection using machine learning models trained on data collected from serious games. Appl Sci (Basel) 2021 Sep;11(17):8184. doi: 10.3390/app11178184. doi. [DOI] [Google Scholar]

[R58] 58.Rutkowski TM, Abe MS, Koculak M, Otake-Matsuura M. Classifying mild cognitive impairment from behavioral responses in emotional arousal and valence evaluation task - AI approach for early dementia biomarker in aging societies. Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:5537–5543. doi: 10.1109/EMBC44109.2020.9175805. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R59] 59.Wu J, Tu J, Liu Z, et al. An effective test (EOmciSS) for screening older adults with mild cognitive impairment in a community setting: development and validation study. J Med Internet Res. 2023 Jan;25:e40858. doi: 10.2196/40858. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R60] 60.Chan JYC, Wong A, Yiu B, et al. Electronic cognitive screen technology for screening older adults with dementia and mild cognitive impairment in a community setting: development and validation study. J Med Internet Res. 2020 Dec 18;22(12):e17332. doi: 10.2196/17332. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R61] 61.Kalafatis C, Modarres MH, Apostolou P, et al. Validity and cultural generalisability of a 5-minute AI-based, computerised cognitive assessment in mild cognitive impairment and Alzheimer’s dementia. Front Psychiatry. 2021;12:706695. doi: 10.3389/fpsyt.2021.706695. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R62] 62.Ghoraani B, Boettcher LN, Hssayeni MD, Rosenfeld A, Tolea MI, Galvin JE. Detection of mild cognitive impairment and Alzheimer’s disease using dual-task gait assessments and machine learning. Biomed Signal Process Control. 2021 Feb;64:102249. doi: 10.1016/j.bspc.2020.102249. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R63] 63.Boettcher LN, Hssayeni M, Rosenfeld A, Tolea MI, Galvin JE, Ghoraani B. Dual-task gait assessment and machine learning for early-detection of cognitive decline. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society; Jul 20-24, 2020; Montreal, QC, Canada. Presented at. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R64] 64.Ward EC, Sharma S, Burns C, Theodoros D, Russell T. Validity of conducting clinical dysphagia assessments for patients with normal to mild cognitive impairment via telerehabilitation. Dysphagia. 2012 Dec;27(4):460–472. doi: 10.1007/s00455-011-9390-9. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R65] 65.Ghani Z, Saha S, Jarl J, Andersson M, Berglund JS, Anderberg P. Short term economic evaluation of the digital platform “Support, Monitoring and Reminder Technology for Mild Dementia” (SMART4MD) for people with mild cognitive impairment and their informal caregivers. J Alzheimers Dis. 2022;86(4):1629–1641. doi: 10.3233/JAD-215013. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R66] 66.Schmitter-Edgecombe M, Brown K, Luna C, et al. Partnering a compensatory application with activity-aware prompting to improve use in individuals with amnestic mild cognitive impairment: a randomized controlled pilot clinical trial. J Alzheimers Dis. 2022;85(1):73–90. doi: 10.3233/JAD-215022. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R67] 67.De Wit L, O’Shea D, Chandler M, et al. Physical exercise and cognitive engagement outcomes for mild neurocognitive disorder: a group-randomized pilot trial. Trials. 2018 Oct 19;19(1):573. doi: 10.1186/s13063-018-2865-3. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R68] 68.Iliadou P, Paliokas I, Zygouris S, et al. A comparison of traditional and serious game-based digital markers of cognition in older adults with mild cognitive impairment and healthy controls. Journal of Alzheimer’s Disease. 2021 Feb 16;79(4):1747–1759. doi: 10.3233/JAD-201300. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R69] 69.Wu J, He Y, Liang S, et al. Computerized cognitive training enhances episodic memory by down-modulating posterior cingulate-precuneus connectivity in older persons with mild cognitive impairment: a randomized controlled trial. Am J Geriatr Psychiatry. 2023 Oct;31(10):820–832. doi: 10.1016/j.jagp.2023.04.008. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R70] 70.Palestra G, Pino O. Detecting emotions during a memory training assisted by a social robot for individuals with mild cognitive impairment (MCI) Multimed Tools Appl. 2020 Dec;79(47-48):35829–35844. doi: 10.1007/s11042-020-10092-4. doi. [DOI] [Google Scholar]

[R71] 71.Teasdale N, Simoneau M, Hudon L, et al. Older adults with mild cognitive impairments show less driving errors after a multiple sessions simulator training program but do not exhibit long term retention. Front Hum Neurosci. 2016;10:653. doi: 10.3389/fnhum.2016.00653. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R72] 72.Chang YL, Luo DH, Huang TR, Goh JOS, Yeh SL, Fu LC. Identifying mild cognitive impairment by using human-robot interactions. Libon D, editor. J Alzheimers Dis. 2022;85(3):1129–1142. doi: 10.3233/JAD-215015. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R73] 73.Pino O, Palestra G, Trevino R, De Carolis B. The humanoid robot NAO as trainer in a memory program for elderly people with mild cognitive impairment. Int J of Soc Robotics. 2020 Jan;12(1):21–33. doi: 10.1007/s12369-019-00533-y. doi. [DOI] [Google Scholar]

[R74] 74.Moussavi Z, Kimura K, Lithgow B. Egocentric spatial orientation differences between Alzheimer’s disease at early stages and mild cognitive impairment: a diagnostic aid. Med Biol Eng Comput. 2022 Feb;60(2):501–509. doi: 10.1007/s11517-021-02478-9. doi. [DOI] [PubMed] [Google Scholar]

[R75] 75.Boller B, Ouellet É, Belleville S. Using virtual reality to assess and promote transfer of memory training in older adults with memory complaints: a randomized controlled trial. Front Psychol. 2021;12:627242. doi: 10.3389/fpsyg.2021.627242. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R76] 76.Hassandra M, Galanis E, Hatzigeorgiadis A, et al. Α virtual reality app for physical and cognitive training of older people with mild cognitive impairment: mixed methods feasibility study. JMIR Serious Games. 2021 Mar 24;9(1):e24170. doi: 10.2196/24170. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R77] 77.Wild KV, Mattek NC, Maxwell SA, Dodge HH, Jimison HB, Kaye JA. Computer‐related self‐efficacy and anxiety in older adults with and without mild cognitive impairment. Alzheimer's & Dementia. 2012 Nov;8(6):544–552. doi: 10.1016/j.jalz.2011.12.008. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R78] 78.Arshad H, Anwar K, Khattak HG, Amjad I, Majeed Y. Effect of brain training game on mild cognitive impairment (MCI) in older adults. [27-11-2025];PJMHS. 2021 Sep 30;15(9):2272–2275. doi: 10.53350/pjmhs211592272. https://pjmhsonline.com/published-issues/2021/september URL. Accessed. doi. [DOI] [Google Scholar]

[R79] 79.Nousia A, Martzoukou M, Petri MC, Messinis L, Nasios G. Face-to-face vs. telerehabilitation language and cognitive training in patients with multi-domain amnestic mild cognitive impairment. Appl Neuropsychol Adult. 2025;32(5):1282–1290. doi: 10.1080/23279095.2023.2259035. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R80] 80.Manenti R, Gobbi E, Baglio F, et al. Effectiveness of an innovative cognitive treatment and telerehabilitation on subjects with mild cognitive impairment: a multicenter, randomized, active-controlled study. Front Aging Neurosci. 2020;12:585988. doi: 10.3389/fnagi.2020.585988. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R81] 81.Wang Y, Chen T, Wang C, et al. A new smart 2-min mobile alerting method for mild cognitive impairment due to Alzheimer’s disease in the community. Brain Sci. 2023 Jan 31;13(2):244. doi: 10.3390/brainsci13020244. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R82] 82.Weniger G, Ruhleder M, Lange C, Wolf S, Irle E. Egocentric and allocentric memory as assessed by virtual reality in individuals with amnestic mild cognitive impairment. Neuropsychologia. 2011 Feb;49(3):518–527. doi: 10.1016/j.neuropsychologia.2010.12.031. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R83] 83.Tarnanas I, Papagiannopoulos S, Kazis D, Wiederhold M, Widerhold B, Tsolaki M. Reliability of a novel serious game using dual-task gait profiles to early characterize aMCI. Front Aging Neurosci. 2015;7:50. doi: 10.3389/fnagi.2015.00050. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R84] 84.Jirayucharoensak S, Israsena P, Pan-Ngum S, Hemrungrojn S, Maes M. A game-based neurofeedback training system to enhance cognitive performance in healthy elderly subjects and in patients with amnestic mild cognitive impairment. Clin Interv Aging. 2019;14:347–360. doi: 10.2147/CIA.S189047. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R85] 85.Savulich G, Piercy T, Fox C, et al. Cognitive training using a novel memory game on an iPad in patients with amnestic mild cognitive impairment (aMCI) Int J Neuropsychopharmacol. 2017 Aug 1;20(8):624–633. doi: 10.1093/ijnp/pyx040. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R86] 86.Kim H, Hong JP, Kang JM, et al. Cognitive reserve and the effects of virtual reality-based cognitive training on elderly individuals with mild cognitive impairment and normal cognition. Psychogeriatrics. 2021 Jul;21(4):552–559. doi: 10.1111/psyg.12705. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R87] 87.Cogné M, Auriacombe S, Vasa L, et al. Are visual cues helpful for virtual spatial navigation and spatial memory in patients with mild cognitive impairment or Alzheimer’s disease? Neuropsychology. 2018 May;32(4):385–400. doi: 10.1037/neu0000435. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R88] 88.Zhao Y, Li L, He X, et al. Psychodynamic-based virtual reality cognitive training system with personalized emotional arousal elements for mild cognitive impairment patients. Comput Methods Programs Biomed. 2023 Nov;241:107779. doi: 10.1016/j.cmpb.2023.107779. doi. [DOI] [PubMed] [Google Scholar]

[R89] 89.Park JH, Liao Y, Kim DR, et al. Feasibility and tolerability of a culture-based virtual reality (VR) training program in patients with mild cognitive impairment: a randomized controlled pilot study. Int J Environ Res Public Health. 2020 Apr 27;17(9):3030. doi: 10.3390/ijerph17093030. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R90] 90.Delmastro F, Martino FD, Dolciotti C. Cognitive training and stress detection in MCI frail older people through wearable sensors and machine learning. IEEE Access. 2020;8:65573–65590. doi: 10.1109/ACCESS.2020.2985301. doi. [DOI] [Google Scholar]

[R91] 91.Gelonch O, Ribera M, Codern-Bové N, et al. Acceptability of a lifelogging wearable camera in older adults with mild cognitive impairment: a mixed-method study. BMC Geriatr. 2019 Apr 16;19(1):110. doi: 10.1186/s12877-019-1132-0. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R92] 92.Locke DEC, Khayoun R, Shandera-Ochsner AL, et al. Innovation inspired by COVID: a virtual treatment program for patients with mild cognitive impairment at Mayo Clinic. Mayo Clin Proc Innov Qual Outcomes. 2021 Oct;5(5):820–826. doi: 10.1016/j.mayocpiqo.2021.06.004. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R93] 93.Lai YL, Chen WY, Hsu LY, Fu CH. The effect of a tele-health intervention program on home-dwelling persons with dementia or MCI and on their primary caregivers during the stay-at-home-order period in the COVID-19 pandemic outbreak: evidence from Taiwan. Healthcare (Basel) 2022 May 24;10(6):969. doi: 10.3390/healthcare10060969. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R94] 94.Finn M, McDonald S. A single case study of computerised cognitive training for older persons with mild cognitive impairment. NeuroRehabilitation. 2014 Jan 1;35(2):261–270. doi: 10.3233/NRE-141121. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R95] 95.Ianculescu M, Paraschiv EA, Alexandru A. Addressing mild cognitive impairment and boosting wellness for the elderly through personalized remote monitoring. Healthcare (Basel) 10(7):1214. doi: 10.3390/healthcare10071214. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R96] 96.Lee LP, Har AWY, Ngai CH, Lai DWL, Lam BYH, Chan CCH. Audiovisual integrative training for augmenting cognitive- motor functions in older adults with mild cognitive impairment. BMC Geriatr. 2020 Feb 17;20(1):64. doi: 10.1186/s12877-020-1465-8. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R97] 97.Cammisuli DM, Isella V, Verde F, et al. Behavioral disorders of spatial cognition in patients with mild cognitive impairment due to Alzheimer’s disease: preliminary findings from the BDSC-MCI project. J Clin Med. 13(4):1178. doi: 10.3390/jcm13041178. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R98] 98.Nousia A, Martzoukou M, Siokas V, et al. Beneficial effect of computer-based multidomain cognitive training in patients with mild cognitive impairment. Applied Neuropsychology: Adult. 2021 Nov 2;28(6):717–726. doi: 10.1080/23279095.2019.1692842. doi. [DOI] [PubMed] [Google Scholar]

[R99] 99.Luna C, Cook DJ, Schmitter-Edgecombe M. But will they use it? Predictors of adoption of an electronic memory aid in individuals with amnestic mild cognitive impairment. Neuropsychology. 37(8):955–965. doi: 10.1037/neu0000898. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R100] 100.Park JH. Can the virtual reality-based spatial memory test better discriminate mild cognitive impairment than neuropsychological assessment? IJERPH. 19(16):9950. doi: 10.3390/ijerph19169950. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R101] 101.Lau CI, Liu MN, Cheng FY, Wang HC, Walsh V, Liao YY. Can transcranial direct current stimulation combined with interactive computerized cognitive training boost cognition and gait performance in older adults with mild cognitive impairment? A randomized controlled trial. J Neuroeng Rehabil. 21(1) doi: 10.1186/s12984-024-01313-0. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R102] 102.Walker G, Morris LA, Christensen H, Mirheidari B, Reuber M, Blackburn DJ. Characterising spoken responses to an intelligent virtual agent by persons with mild cognitive impairment. Clin Linguist Phon. 2021 Mar 4;35(3):237–252. doi: 10.1080/02699206.2020.1777586. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R103] 103.Lin F, Heffner KL, Ren P, et al. Cognitive and neural effects of vision-based speed-of-processing training in older adults with amnestic mild cognitive impairment: a pilot study. [27-11-2025];J Am Geriatr Soc. 2016 Jun;64(6):1293–1298. doi: 10.1111/jgs.14132. https://agsjournals.onlinelibrary.wiley.com/toc/15325415/64/6 URL. Accessed. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R104] 104.Kim JH, Han JY, Park GC, Lee JS. Cognitive improvement effects of electroacupuncture combined with computer-based cognitive rehabilitation in patients with mild cognitive impairment: a randomized controlled trial. Brain Sci. 10(12):984. doi: 10.3390/brainsci10120984. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R105] 105.Han E, Park J, Kim H, Jo G, Do HK, Lee BI. Cognitive intervention with musical stimuli using digital devices on mild cognitive impairment: a pilot study. Healthcare (Basel) 8(1):45. doi: 10.3390/healthcare8010045. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R106] 106.Lee I, Kim D, Kim S, Kim HJ, Chung US, Lee JJ. Cognitive training based on functional near-infrared spectroscopy neurofeedback for the elderly with mild cognitive impairment: a preliminary study. Front Aging Neurosci. 15 doi: 10.3389/fnagi.2023.1168815. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R107] 107.Hyer L, Scott C, Atkinson MM, et al. Cognitive training program to improve working memory in older adults with MCI. Clin Gerontol. 2016;39(5):410–427. doi: 10.1080/07317115.2015.1120257. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R108] 108.Barnes DE, Yaffe K, Belfor N, et al. Computer-based cognitive training for mild cognitive impairment. Alzheimer Disease & Associated Disorders. 2009;23(3):205–210. doi: 10.1097/WAD.0b013e31819c6137. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R109] 109.Finn M, McDonald S. Computerised cognitive training for older persons with mild cognitive impairment: a pilot study using a randomised controlled trial design. Brain Impair. 2011 Dec 1;12(3):187–199. doi: 10.1375/brim.12.3.187. doi. [DOI] [Google Scholar]

[R110] 110.Dowell-Esquivel C, Czaja SJ, Kallestrup P, Depp CA, Saber JN, Harvey PD. Computerized cognitive and skills training in older people with mild cognitive impairment: using ecological momentary assessment to index treatment-related changes in real-world performance of technology-dependent functional tasks. Am J Geriatr Psychiatry. 2024 Apr;32(4):446–459. doi: 10.1016/j.jagp.2023.10.014. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R111] 111.Djabelkhir L, Wu YH, Vidal JS, et al. Computerized cognitive stimulation and engagement programs in older adults with mild cognitive impairment: comparing feasibility, acceptability, and cognitive and psychosocial effects. Clin Interv Aging. 2017;12:1967–1975. doi: 10.2147/CIA.S145769. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R112] 112.Li BY, He NY, Qiao Y, et al. Computerized cognitive training for Chinese mild cognitive impairment patients: a neuropsychological and fMRI study. Neuroimage Clin. 2019;22:101691. doi: 10.1016/j.nicl.2019.101691. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R113] 113.Duff K, Ying J, Suhrie KR, et al. Computerized cognitive training in amnestic mild cognitive impairment: a randomized clinical trial. J Geriatr Psychiatry Neurol. 2022 May;35(3):400–409. doi: 10.1177/08919887211006472. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R114] 114.Nwosu A, Qian M, Phillips J, et al. Computerized cognitive training in mild cognitive impairment: findings in African Americans and Caucasians. J Prev Alzheimers Dis. 2024;11(1):149–154. doi: 10.14283/jpad.2023.80. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R115] 115.Raghunath N, Dahmen J, Brown K, Cook D, Schmitter-Edgecombe M. Creating a digital memory notebook application for individuals with mild cognitive impairment to support everyday functioning. Disability and Rehabilitation: Assistive Technology. 2020 May 18;15(4):421–431. doi: 10.1080/17483107.2019.1587017. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R116] 116.Castilla D, Suso-Ribera C, Zaragoza I, Garcia-Palacios A, Botella C. Designing ICTs for users with mild cognitive impairment: a usability study. Int J Environ Res Public Health. 17(14):5153. doi: 10.3390/ijerph17145153. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R117] 117.Diaz Baquero AA, Perea Bartolomé MV, Toribio-Guzmán JM, et al. Determinants of adherence to a “GRADIOR” computer-based cognitive training program in people with mild cognitive impairment (MCI) and mild dementia. J Clin Med. 11(6):1714. doi: 10.3390/jcm11061714. doi. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R118] 118.Yang HL, Chu H, Kao CC, et al. Development and effectiveness of virtual interactive working memory training for older people with mild cognitive impairment: a single-blind randomised controlled trial. Age Ageing. 2019 Jul 1;48(4):519–525. doi: 10.1093/ageing/afz029. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R119] 119.Park JH. Does the virtual shopping training improve executive function and instrumental activities of daily living of patients with mild cognitive impairment? Asian J Psychiatr. 2022 Mar;69:102977. doi: 10.1016/j.ajp.2021.102977. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R120] 120.Simfukwe C, Youn YC, Kim SY, An SS. Digital trail making test-black and white: normal vs MCI. Appl Neuropsychol Adult. 2022;29(6):1296–1303. doi: 10.1080/23279095.2021.1871615. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R121] 121.Harvey PD, Dowell-Esquivel C, Macchiarelli JE, Martinez A, Kallestrup P, Czaja SJ. Early prediction of mastery of a computerized functional skills training program in participants with mild cognitive impairment. Int Psychogeriatr. 2024 Dec;36(12):1182–1193. doi: 10.1017/S1041610224000115. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R122] 122.Amjad I, Toor H, Niazi IK, et al. Xbox 360 Kinect cognitive games improve slowness, complexity of EEG, and cognitive functions in subjects with mild cognitive impairment: a randomized control trial. Games Health J. 2019 Apr;8(2):144–152. doi: 10.1089/g4h.2018.0029. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R123] 123.Park E, Yun BJ, Min YS, et al. Effects of a mixed reality-based cognitive training system compared to a conventional computer-assisted cognitive training system on mild cognitive impairment: a pilot study. Cogn Behav Neurol. 2019 Sep;32(3):172–178. doi: 10.1097/WNN.0000000000000197. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R124] 124.Kim S, Park E, Cha H, Jung JC, Jung TD, Chang Y. Effects of cognitive training in mild cognitive impairment measured by resting state functional imaging. Behav Sci (Basel) 2020 Nov 17;10(11):175. doi: 10.3390/bs10110175. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R125] 125.Mirza RA, Yaqoob I. Effects of combined aerobic and virtual reality-based cognitive training on 76 years old diabetic male with mild cognitive impairment. J Coll Physicians Surg Pak. 2018 Sep;28(9):S210–S212. doi: 10.29271/jcpsp.2018.09.S210. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R126] 126.Mrakic-Sposta S, Di Santo SG, Franchini F, et al. Effects of combined physical and cognitive virtual reality-based training on cognitive impairment and oxidative stress in MCI patients: a pilot study. Front Aging Neurosci. 2018;10:282. doi: 10.3389/fnagi.2018.00282. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R127] 127.Wu J, He Y, Liang S, et al. Effects of computerized cognitive training on structure‒function coupling and topology of multiple brain networks in people with mild cognitive impairment: a randomized controlled trial. Alzheimers Res Ther. 2023 Sep 23;15(1):158. doi: 10.1186/s13195-023-01292-9. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R128] 128.Sato K, Ochi A, Watanabe K, Yamada K. Effects of dance video game training on cognitive functions of community-dwelling older adults with mild cognitive impairment. Aging Clin Exp Res. 2023 May;35(5):987–994. doi: 10.1007/s40520-023-02374-2. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R129] 129.Lim EH, Kim DS, Won YH, et al. Effects of home based serious game training (Brain Talk TM) in the elderly with mild cognitive impairment: randomized, a single-blind, controlled trial. Brain Neurorehabil. 2023 Mar;16(1):e4. doi: 10.12786/bn.2023.16.e4. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R130] 130.Baik JS, Min JH, Ko SH, et al. Effects of home-based computerized cognitive training in community-dwelling adults with mild cognitive impairment. IEEE J Transl Eng Health Med. 2024;12:97–105. doi: 10.1109/JTEHM.2023.3317189. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R131] 131.Park JH. Effects of spatial cognitive training using virtual reality on hippocampal functions and prefrontal cortex activity in older adults with mild cognitive impairment. [27-11-2025];Int J Gerontol. 2022 16(3):242–246. doi: 10.6890/IJGE.202207_16(3).0014. http://www.sgecm.org.tw/ijge/journal/detail.asp?id=504&title=Effects%20of%20Spatial%20Cognitive%20Training%20Using%20Virtual%20Reality%20on%20Hippocampal%20Functions%20and%20Prefrontal%20Cortex%20Activity%20in%20Older%20Adults%20with%20Mild%20Cognitive%20Impairment URL. Accessed. doi. [DOI] [Google Scholar]

[R132] 132.Çinar N, Şahiner TAH. Effects of the online computerized cognitive training program BEYNEX on the cognitive tests of individuals with subjective cognitive impairment and Alzheimer’s disease on rivastigmine therapy. Turk J Med Sci. 2020 Feb 13;50(1):231–238. doi: 10.3906/sag-1905-244. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R133] 133.Baldimtsi E, Mouzakidis C, Karathanasi EM, et al. Effects of virtual reality physical and cognitive training intervention on cognitive abilities of elders with mild cognitive impairment. J Alzheimers Dis Rep. 2023;7(1):1475–1490. doi: 10.3233/ADR-230099. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R134] 134.Liao YY, Chen IH, Lin YJ, Chen Y, Hsu WC. Effects of virtual reality-based physical and cognitive training on executive function and dual-task gait performance in older adults with mild cognitive impairment: a randomized control trial. Front Aging Neurosci. 2019;11:162. doi: 10.3389/fnagi.2019.00162. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R135] 135.Park JH. Effects of virtual reality-based spatial cognitive training on hippocampal function of older adults with mild cognitive impairment. Int Psychogeriatr. 2022 Feb;34(2):157–163. doi: 10.1017/S1041610220001131. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R136] 136.Alegret M, Espinosa A, Ortega G, et al. From face-to-face to home-to-home: validity of a teleneuropsychological battery. J Alzheimers Dis. 2021;81(4):1541–1553. doi: 10.3233/JAD-201389. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R137] 137.Pereira-Morales AJ, Cruz-Salinas AF, Aponte J, Pereira-Manrique F. Efficacy of a computer-based cognitive training program in older people with subjective memory complaints: a randomized study. Int J Neurosci. 2018 Jan;128(1):1–9. doi: 10.1080/00207454.2017.1308930. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R138] 138.Ramnath U, Rauch L, Lambert EV, Kolbe-Alexander T. Efficacy of interactive video gaming in older adults with memory complaints: a cluster-randomized exercise intervention. PLoS ONE. 2021;16(5):e0252016. doi: 10.1371/journal.pone.0252016. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R139] 139.Jones KT, Ostrand AE, Gazzaley A, Zanto TP. Enhancing cognitive control in amnestic mild cognitive impairment via at-home non-invasive neuromodulation in a randomized trial. Sci Rep. 2023 May 8;13(1):7435. doi: 10.1038/s41598-023-34582-1. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R140] 140.Shamir D, Loubani K, Schaham NG, Buckman Z, Rand D. Experiences of older adults with mild cognitive impairment from cognitive self-training using touchscreen tablets. Games Health J. 2024 Feb;13(1):13–24. doi: 10.1089/g4h.2023.0017. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R141] 141.Li N, Yang X, Du W, et al. Exploratory research on key technology of human-computer interactive 2.5-minute fast digital early warning for mild cognitive impairment. Comput Intell Neurosci. 2022;2022:2495330. doi: 10.1155/2022/2495330. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R142] 142.Goumopoulos C, Skikos G, Frounta M. Feasibility and effects of cognitive training with the COGNIPLAT game platform in elderly with mild cognitive impairment: pilot randomized controlled trial. Games Health J. 2023 Oct;12(5):414–425. doi: 10.1089/g4h.2023.0029. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R143] 143.Sachs BC, Latham LA, Bateman JR, et al. Feasibility of remote administration of the uniform data set-version 3 for assessment of older adults with mild cognitive impairment and Alzheimer’s disease. Arch Clin Neuropsychol. 2024 Jul 24;39(5):635–643. doi: 10.1093/arclin/acae001. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R144] 144.Zhu K, Zhang Q, He B, Huang M, Lin R, Li H. Immersive virtual reality-based cognitive intervention for the improvement of cognitive function, depression, and perceived stress in older adults with mild cognitive impairment and mild dementia: pilot pre-post study. JMIR Serious Games. 2022 Feb 21;10(1):e32117. doi: 10.2196/32117. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R145] 145.Harvey PD, Chirino M, Mueller A, et al. Improvements in performance based measures of functional capacity and cognition after computerized functional skills training in older people with mild cognitive impairment and healthy comparators. Psychiatry Res. 2024 Apr;334:115792. doi: 10.1016/j.psychres.2024.115792. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R146] 146.Dodge HH, Yu K, Wu CY, et al. Internet-based conversational engagement randomized controlled clinical trial (I-CONECT) among socially isolated adults 75+ years old with normal cognition or mild cognitive impairment: topline results. Gerontologist. 2024 Apr 1;64(4):gnad147. doi: 10.1093/geront/gnad147. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R147] 147.Damirchi A, Hosseini F, Babaei P. Mental training enhances cognitive function and BDNF more than either physical or combined training in elderly women with MCI: a small-scale study. Am J Alzheimers Dis Other Demen. 2018 Feb;33(1):20–29. doi: 10.1177/1533317517727068. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R148] 148.Styliadis C, Kartsidis P, Paraskevopoulos E, Ioannides AA, Bamidis PD. Neuroplastic effects of combined computerized physical and cognitive training in elderly individuals at risk for dementia: an eLORETA controlled study on resting states. Neural Plast. 2015;2015:172192. doi: 10.1155/2015/172192. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R149] 149.Oh MW, Ki YJ, Jeon BH, et al. Nurse-led computerized cognitive training for mild cognitive impairment: a preliminary study. Rehabil Nurs. 2020 Apr 15; doi: 10.1097/RNJ.0000000000000264. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R150] 150.Herrera C, Chambon C, Michel BF, Paban V, Alescio-Lautier B. Positive effects of computer-based cognitive training in adults with mild cognitive impairment. Neuropsychologia. 2012 Jul;50(8):1871–1881. doi: 10.1016/j.neuropsychologia.2012.04.012. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R151] 151.Mendoza Laiz N, Del Valle Díaz S, Rioja Collado N, Gomez-Pilar J, Hornero R. Potential benefits of a cognitive training program in mild cognitive impairment (MCI) Restor Neurol Neurosci. 2018;36(2):207–213. doi: 10.3233/RNN-170754. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R152] 152.Hackett K, Lehman S, Divers R, et al. Remind me to remember: a pilot study of a novel smartphone reminder application for older adults with dementia and mild cognitive impairment. Neuropsychol Rehabil. 2022 Jan;32(1):22–50. doi: 10.1080/09602011.2020.1794909. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R153] 153.Wu R, Li A, Xue C, et al. Screening for mild cognitive impairment with speech interaction based on virtual reality and wearable devices. Brain Sci. 2023 Aug 21;13(8):1222. doi: 10.3390/brainsci13081222. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R154] 154.Formica C, Bonanno M, Sorbera C, et al. Smartphone-based cognitive telerehabilitation: a usability and feasibility study focusing on mild cognitive impairment. Sensors (Basel) 2024 Jan 15;24(2):525. doi: 10.3390/s24020525. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R155] 155.Liu H, Yang X, Wang X, Yang X, Zhang X, Li Q. Study on adjuvant medication for patients with mild cognitive impairment based on VR technology and health education. Contrast Media Mol Imaging. 2021;2021:1187704. doi: 10.1155/2021/1187704. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R156] 156.Bekrater-Bodmann R, Löffler A, Silvoni S, et al. Tablet-based sensorimotor home-training system for amnestic mild cognitive impairments in the elderly: design of a randomised clinical trial. BMJ Open. 2019 Aug 2;9(8):e028632. doi: 10.1136/bmjopen-2018-028632. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R157] 157.Wang C, Liu S, Li A, Liu J. Text dialogue analysis for primary screening of mild cognitive impairment: development and validation study. J Med Internet Res. 2023 Dec 29;25:e51501. doi: 10.2196/51501. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R158] 158.Anderson-Hanley C, Barcelos NM, Zimmerman EA, et al. The Aerobic and Cognitive Exercise Study (ACES) for community-dwelling older adults with or at-risk for mild cognitive impairment (MCI): neuropsychological, neurobiological and neuroimaging outcomes of a randomized clinical trial. Front Aging Neurosci. 2018;10:76. doi: 10.3389/fnagi.2018.00076. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R159] 159.Givon Schaham N, Vitek H, Donda N, Elbo Golan I, Buckman Z, Rand D. The development and feasibility of TECH: Tablet Enhancement of Cognition and Health, a novel cognitive intervention for people with mild cognitive impairment. Games Health J. 2020 Oct;9(5):346–352. doi: 10.1089/g4h.2019.0157. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R160] 160.Thapa N, Park HJ, Yang JG, et al. The effect of a virtual reality-based intervention program on cognition in older adults with mild cognitive impairment: a randomized control trial. J Clin Med. 2020 Apr 29;9(5):1283. doi: 10.3390/jcm9051283. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R161] 161.Oh W, Park H, Hallett M, You JSH. The effectiveness of a multimodal brain empowerment program in mild cognitive impairment: a single-blind, quasi-randomized experimental study. J Clin Med. 2023 Jul 26;12(15):4895. doi: 10.3390/jcm12154895. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R162] 162.Torpil B, Şahin S, Pekçetin S, Uyanık M. The effectiveness of a virtual reality-based intervention on cognitive functions in older adults with mild cognitive impairment: a single-blind, randomized controlled trial. Games Health J. 2021 Apr;10(2):109–114. doi: 10.1089/g4h.2020.0086. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R163] 163.Torpil B, Pekçetin E, Pekçetin S. The effectiveness of cognitive rehabilitation intervention with the telerehabilitation method for amnestic mild cognitive impairment: a feasibility randomized controlled trial. J Telemed Telecare. 2025 Apr;31(3):320–327. doi: 10.1177/1357633X231189541. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R164] 164.González-Palau F, Franco M, Bamidis P, et al. The effects of a computer-based cognitive and physical training program in a healthy and mildly cognitive impaired aging sample. Aging Ment Health. 2014 Sep;18(7):838–846. doi: 10.1080/13607863.2014.899972. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R165] 165.Choi W, Lee S. The effects of virtual kayak paddling exercise on postural balance, muscle performance, and cognitive function in older adults with mild cognitive impairment: a randomized controlled trial. J Aging Phys Act. 2019 Dec 1;27(4):861–870. doi: 10.1123/japa.2018-0020. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R166] 166.Lai CH, Pai MC. The feasibility and practicality of auxiliary detection of spatial navigation impairment in patients with mild cognitive impairment due to Alzheimer’s disease by using virtual reality. Heliyon. 2024 Feb 15;10(3):e24748. doi: 10.1016/j.heliyon.2024.e24748. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R167] 167.Park EA, Jung AR, Lee KA. The humanoid robot Sil-Bot in a cognitive training program for community-dwelling elderly people with mild cognitive impairment during the COVID-19 pandemic: a randomized controlled trial. Int J Environ Res Public Health. 2021 Aug 3;18(15):8198. doi: 10.3390/ijerph18158198. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R168] 168.Manca M, Paternò F, Santoro C, et al. The impact of serious games with humanoid robots on mild cognitive impairment older adults. Int J Hum Comput Stud. 2021 Jan;145:102509. doi: 10.1016/j.ijhcs.2020.102509. doi. [DOI] [Google Scholar]

[R169] 169.Cabinio M, Rossetto F, Isernia S, et al. The use of a virtual reality platform for the assessment of the memory decline and the hippocampal neural injury in subjects with mild cognitive impairment: the validity of Smart Aging Serious Game (SASG) J Clin Med. 2020 May 6;9(5):1355. doi: 10.3390/jcm9051355. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R170] 170.Sheehy L, Sveistrup H, Knoefel F, et al. The use of home-based nonimmersive virtual reality to encourage physical and cognitive exercise in people with mild cognitive impairment: a feasibility study. J Aging Phys Act. 2022 Apr 1;30(2):297–307. doi: 10.1123/japa.2021-0043. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R171] 171.Vermeij A, Claassen J, Dautzenberg PLJ, Kessels RPC. Transfer and maintenance effects of online working-memory training in normal ageing and mild cognitive impairment. Neuropsychol Rehabil. 2016 Oct;26(5-6):783–809. doi: 10.1080/09602011.2015.1048694. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R172] 172.Li A, Xue C, Wu R, Wu W, Zhao J, Qiang Y. Unearthing subtle cognitive variations: a digital screening tool for detecting and monitoring mild cognitive impairment. International Journal of Human–Computer Interaction. 2025 Feb 16;41(4):2579–2599. doi: 10.1080/10447318.2024.2327179. doi. [DOI] [Google Scholar]

[R173] 173.Tuena C, Serino S, Stramba-Badiale C, et al. Usability of an embodied CAVE system for spatial navigation training in mild cognitive impairment. J Clin Med. 2023 Mar 1;12(5):1949. doi: 10.3390/jcm12051949. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R174] 174.Bourrelier J, Ryard J, Dion M, Merienne F, Manckoundia P, Mourey F. Use of a virtual environment to engage motor and postural abilities in elderly subjects with and without mild cognitive impairment (MAAMI Project) IRBM. 2016 Apr;37(2):75–80. doi: 10.1016/j.irbm.2016.02.007. doi. [DOI] [Google Scholar]

[R175] 175.Werner P, Rabinowitz S, Klinger E, Korczyn AD, Josman N. Use of the virtual action planning supermarket for the diagnosis of mild cognitive impairment: a preliminary study. Dement Geriatr Cogn Disord. 2009;27(4):301–309. doi: 10.1159/000204915. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R176] 176.Mondellini M, Arlati S, Gapeyeva H, et al. User experience during an immersive virtual reality-based cognitive task: a comparison between Estonian and Italian older adults with MCI. Sensors (Basel) 2022 Oct 27;22(21):8249. doi: 10.3390/s22218249. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R177] 177.Plancher G, Tirard A, Gyselinck V, Nicolas S, Piolino P. Using virtual reality to characterize episodic memory profiles in amnestic mild cognitive impairment and Alzheimer’s disease: influence of active and passive encoding. Neuropsychologia. 2012 Apr;50(5):592–602. doi: 10.1016/j.neuropsychologia.2011.12.013. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R178] 178.Mohammadi A, Kargar M, Hesami E. Using virtual reality to distinguish subjects with multiple- but not single-domain amnestic mild cognitive impairment from normal elderly subjects. Psychogeriatrics. 2018 Mar;18(2):132–142. doi: 10.1111/psyg.12301. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R179] 179.Liao YY, Tseng HY, Lin YJ, Wang CJ, Hsu WC. Using virtual reality-based training to improve cognitive function, instrumental activities of daily living and neural efficiency in older adults with mild cognitive impairment. Eur J Phys Rehabil Med. 2020 Feb;56(1):47–57. doi: 10.23736/S1973-9087.19.05899-4. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R180] 180.Skirrow C, Meszaros M, Meepegama U, et al. Validation of a remote and fully automated story recall task to assess for early cognitive impairment in older adults: longitudinal case-control observational study. JMIR Aging. 2022 Sep 30;5(3):e37090. doi: 10.2196/37090. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R181] 181.Cerino ES, Katz MJ, Wang C, et al. Variability in cognitive performance on mobile devices is sensitive to mild cognitive impairment: results from the Einstein Aging Study. Front Digit Health. 2021;3:758031. doi: 10.3389/fdgth.2021.758031. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R182] 182.Seo K, Kim JK, Oh DH, Ryu H, Choi H. Virtual daily living test to screen for mild cognitive impairment using kinematic movement analysis. PLoS ONE. 2017;12(7):e0181883. doi: 10.1371/journal.pone.0181883. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R183] 183.Yang JG, Thapa N, Park HJ, et al. Virtual reality and exercise training enhance brain, cognitive, and physical health in older adults with mild cognitive impairment. Int J Environ Res Public Health. 2022 Oct 15;19(20):13300. doi: 10.3390/ijerph192013300. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R184] 184.Park JS, Jung YJ, Lee G. Virtual reality-based cognitive-motor rehabilitation in older adults with mild cognitive impairment: a randomized controlled study on motivation and cognitive function. Healthcare (Basel) 2020 Sep 11;8(3):335. doi: 10.3390/healthcare8030335. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R185] 185.Jang S, Choi SW, Son SJ, et al. Virtual reality-based monitoring test for MCI: a multicenter feasibility study. Front Psychiatry. 2022;13:1057513. doi: 10.3389/fpsyt.2022.1057513. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R186] 186.Formica C, Giambò FM, Latella D, et al. Humanoid robots for psychological assessment in mild cognitive impairment: from evaluation to the future of AI-driven data prediction systems. Front Psychol. 2025;16:1579626. doi: 10.3389/fpsyg.2025.1579626. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R187] 187.Fu Y, Wang H. Clinical observation of VR virtual reality rehabilitation training combined with acupuncture in the treatment of mild cognitive impairment. SLAS Technol. 2025 Apr;31:100250. doi: 10.1016/j.slast.2025.100250. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R188] 188.Jones CD, Wasilko R, Zhang G, et al. Detecting sleep/wake rhythm disruption related to cognition in older adults with and without mild cognitive impairment using the myRhythmWatch platform: feasibility and correlation study. JMIR Aging. 2025 Apr 7;8:e67294. doi: 10.2196/67294. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R189] 189.Carvalho CM, Poltronieri BC, Reuwsaat K, Reis MEA, Panizzutti R. Digital cognitive training for functionality in mild cognitive impairment: a randomized controlled clinical trial. Geroscience. 2025 Jun;47(3):5111–5121. doi: 10.1007/s11357-024-01464-x. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R190] 190.Lin LC, Liao JY, Huang CM, et al. Effectiveness of robot-assisted board games on cognitive function and mental health for older adults with mild cognitive impairment: a cluster randomized trial. Games Health J. 2025 Aug;14(4):321–331. doi: 10.1089/g4h.2024.0207. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R191] 191.Buele J, Avilés-Castillo F, Del-Valle-Soto C, Varela-Aldás J, Palacios-Navarro G. Effects of a dual intervention (motor and virtual reality-based cognitive) on cognition in patients with mild cognitive impairment: a single-blind, randomized controlled trial. J Neuroeng Rehabil. 2024 Aug 1;21(1):130. doi: 10.1186/s12984-024-01422-w. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R192] 192.Zhu D, Al Mahmud A, Liu W. Effects of a mobile storytelling app (Huiyou) on social participation among people with mild cognitive impairment: pilot randomized controlled trial. JMIR Hum Factors. 2025 Jun 18;12:e70177. doi: 10.2196/70177. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R193] 193.von Bosse A, Thum A, Mahler S, Schulz H, Weuthen P, Kunze C. Evaluating the feasibility of a dyadic, touch-based multimedia tablet intervention and its effects on the caregiver-patient relationship among individuals with mild cognitive impairment: qualitative triangulation study. JMIR Aging. 2025 Aug 28;8:e75189. doi: 10.2196/75189. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R194] 194.Chen X, Jiang D, Ning H, et al. The experience of and needs for exergames in older adults with mild cognitive impairment: qualitative interview study. JMIR Serious Games. 2025 Jun 17;13:e53631. doi: 10.2196/53631. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R195] 195.Ip WK, Soar J, Fong K, Wang SY, James C. An exploratory study on virtual reality technology for fall prevention in older adults with mild cognitive impairment. Sensors (Basel) 2025 May 15;25(10):3123. doi: 10.3390/s25103123. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R196] 196.Zhang S, Wu M, Sun R, et al. Exploring the discontinuous usage behavior of digital cognitive training among older adults with mild cognitive impairment and their family members: qualitative study using the extended model of IT continuance. J Med Internet Res. 2025 Mar 25;27:e66393. doi: 10.2196/66393. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R197] 197.Kang JM, Kim N, Yun SK, et al. Exploring transfer effects on memory and its neural mechanisms through a computerized cognitive training in mild cognitive impairment: randomized controlled trial. Psychogeriatrics. 2024 Sep;24(5):1075–1086. doi: 10.1111/psyg.13161. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R198] 198.Demiris G, Harrison S, Sefcik J, Skubic M, Richmond TS, Hodgson NA. Feasibility and acceptability of a technology-mediated fall risk prevention intervention for older adults with mild cognitive impairment. J Gerontol A Biol Sci Med Sci. 2025 May 5;80(6):glaf043. doi: 10.1093/gerona/glaf043. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R199] 199.Petri MC, Messinis L, Patrikelis P, et al. Feasibility and clinical effectiveness of computer-based cognitive rehabilitation in illiterate and low-educated individuals with mild cognitive impairment: preliminary data. Arch Clin Neuropsychol. 2025 Apr 27;40(3):382–393. doi: 10.1093/arclin/acae078. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R200] 200.Latella D, Formica C, Ielo A, et al. A feasibility and usability study of a virtual reality tool (VESPA 2.0) for cognitive rehabilitation in patients with mild cognitive impairment: an ecological approach. Front Psychol. 2024;15:1402894. doi: 10.3389/fpsyg.2024.1402894. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R201] 201.Murata N, Nishii S, Usuha R, et al. A gamified N-back app for identifying mild-cognitive impairment in older adults. JMA J. 2025 Jan 15;8(1):174–182. doi: 10.31662/jmaj.2024-0217. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R202] 202.Van Assche M, Petrovic M, Cambier D, et al. Socially assistive robots in aged care: expectations of older adults with MCI in assisted living facilities and their caregivers. Int J of Soc Robotics. 2024 Apr;16(4):687–698. doi: 10.1007/s12369-024-01115-3. doi. [DOI] [Google Scholar]

[R203] 203.Graessel E, Jank M, Scheerbaum P, Scheuermann JS, Pendergrass A. Individualised computerised cognitive training (iCCT) for community-dwelling people with mild cognitive impairment (MCI): results on cognition in the 6-month intervention period of a randomised controlled trial (MCI-CCT study) BMC Med. 2024 Oct 15;22(1):472. doi: 10.1186/s12916-024-03647-x. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R204] 204.Dumurgier J, Paquet C, Hugon J, et al. MemScreen: a smartphone application for detection of mild cognitive impairment: a validation study: smartphone app for MCI detection. J Prev Alzheimers Dis. 2025 Mar;12(3):100077. doi: 10.1016/j.tjpad.2025.100077. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R205] 205.McGarry A, Roesler O, Liscombe J, et al. Much more than the malady: the promise of a web-based digital platform incorporating self-report for research and clinical care in mild cognitive impairment. Mayo Clin Proc Digit Health. 2025 Jun;3(2):100224. doi: 10.1016/j.mcpdig.2025.100224. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R206] 206.Choi Y, Lim JS, Choi H, et al. Narrative mobile video game-based cognitive training to enhance frontal function in patients with mild cognitive impairment. Sci Rep. 2025 Jan 2;15(1):195. doi: 10.1038/s41598-024-84086-9. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R207] 207.Chang CH, Huang KY, Kuo LH, et al. Pilot randomized controlled study on the effectiveness of a virtual reality-based dementia prevention program using self-regulated learning strategies among older adults with mild cognitive impairment. Healthcare (Basel) 2025 May 7;13(9):1082. doi: 10.3390/healthcare13091082. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R208] 208.Ferizaj D, Stamm O, Perotti L, et al. Preliminary effects of mobile computerized cognitive training in adults with mild cognitive impairment: interim analysis of a randomized controlled trial. BMC Psychol. 2025 Mar 5;13(1):202. doi: 10.1186/s40359-025-02458-w. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R209] 209.Butler PM, Yang J, Brown R, et al. Smartwatch- and smartphone-based remote assessment of brain health and detection of mild cognitive impairment. Nat Med. 2025 Mar;31(3):829–839. doi: 10.1038/s41591-024-03475-9. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R210] 210.Ruzi R, Pan Y, Ng ML, et al. A speech-based mobile screening tool for mild cognitive impairment: technical performance and user engagement evaluation. Bioengineering (Basel) 2025 Jan 24;12(2):108. doi: 10.3390/bioengineering12020108. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R211] 211.Jornkokgoud K, Makmee P, Wongupparaj P, Grecucci A. Tablet- and group-based multicomponent cognitive stimulation for older adults with mild cognitive impairment: single-group pilot study and protocol for randomized controlled trial. JMIR Res Protoc. 2025 Feb 21;14:e64465. doi: 10.2196/64465. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R212] 212.Ip WK, Soar J, James C, Wang SY, Fong KNK. Virtual reality game-based training for preventing falls among community-dwelling older adults with mild cognitive impairment: a pilot randomized control trial study. Virtual Real. 29(1) doi: 10.1007/s10055-024-01084-y. doi. [DOI] [Google Scholar]

[R213] 213.Makmee P, Wongupparaj P. VR cognitive-based intervention for enhancing cognitive functions and well-being in older adults with mild cognitive impairment: behavioral and EEG evidence. Psychosoc Interv. 2025 Jan;34(1):37–51. doi: 10.5093/pi2025a4. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R214] 214.Beentjes KM, Neal DP, Kerkhof YJF, et al. Impact of the FindMyApps program on people with mild cognitive impairment or dementia and their caregivers; an exploratory pilot randomised controlled trial. Disabil Rehabil Assist Technol. 2023 Apr;18(3):253–265. doi: 10.1080/17483107.2020.1842918. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R215] 215.Seelye AM, Wild KV, Larimer N, Maxwell S, Kearns P, Kaye JA. Reactions to a remote-controlled video-communication robot in seniors’ homes: a pilot study of feasibility and acceptance. Telemed J E Health. 2012 Dec;18(10):755–759. doi: 10.1089/tmj.2012.0026. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R216] 216.The difference between screening and diagnostic tests. UCLA Health. Aug 19, 2022. [02-08-2024]. https://www.uclahealth.org/news/article/the-difference-between-screening-and-diagnostic-tests URL. Accessed.

[R217] 217.Wübker A, Zwakhalen SMG, Challis D, et al. Costs of care for people with dementia just before and after nursing home placement: primary data from eight European countries. Eur J Health Econ. 2015 Sep;16(7):689–707. doi: 10.1007/s10198-014-0620-6. doi. Medline. [DOI] [PubMed] [Google Scholar]

[R218] 218.Roberto KA, McCann BR, Savla J, Blieszner R. Family caregivers’ management of behavioral expressions of dementia. Gerontologist. 2024 Jun 1;64(6):gnae020. doi: 10.1093/geront/gnae020. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R219] 219.Fisher GG, Franks MM, Plassman BL, et al. Caring for individuals with dementia and cognitive impairment, not dementia: findings from the aging, demographics, and memory study. J Am Geriatr Soc. 2011 Mar;59(3):488–494. doi: 10.1111/j.1532-5415.2010.03304.x. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R220] 220.Winblad B, Amouyel P, Andrieu S, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol. 2016 Apr;15(5):455–532. doi: 10.1016/S1474-4422(16)00062-4. doi. [DOI] [PubMed] [Google Scholar]

[R221] 221.Lindeza P, Rodrigues M, Costa J, Guerreiro M, Rosa MM. Impact of dementia on informal care: a systematic review of family caregivers’ perceptions. BMJ Support Palliat Care. 2024 May;14(e1):e38–e49. doi: 10.1136/bmjspcare-2020-002242. doi. [DOI] [PubMed] [Google Scholar]

[R222] 222.Petersen RC, Lopez O, Armstrong MJ, et al. Practice guideline update summary: mild cognitive impairment [RETIRED]: report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology (ECronicon) 2018 Jan 16;90(3):126–135. doi: 10.1212/WNL.0000000000004826. doi. Medline. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Digital Health Technologies Applied in Patients With Early Cognitive Change: Scoping Review

Yunhao Zhang, MSc

Xuejiao Zhu, PhD

Shulan Yang, MSc

Arkers Kwan Ching Wong, PhD

Xinming Chen, MSc

Abstract

Background

Objective

Methods

Results

Conclusions

Introduction

Background

Research Problem and Aim

Methods

Overview

Identification of the Relevant Studies

Study Selection

Data Extraction

Collating, Summarizing, and Reporting the Findings

Results

Literature Search

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram for study selection.

Characteristics of the Included Studies

Figure 2. Trend analysis of different study designs in DHTs applied in patients with early cognitive change (2009‐2025). DHT: digital health technology.

Type of DHTs Implemented in Patients With Early Cognitive Change

Figure 3. Distribution of study populations in DHT research: patients with MCI, patients with SCD, and caregivers (2009‐2025). DHT: digital health technology; MCI: mild cognitive impairment; SCD: subjective cognitive decline.

Figure 4. The evolving landscape of DHTs in early cognitive change research: trends in the use of 6 types (2009‐2025). DHT: digital health technology; IoT: interet of things.

Outcomes of DHTs in Patients With Early Cognitive Change

Figure 5. Mapping reported outcomes to DHT types in early cognitive change research (2009‐2025).

Discussion

Principal Findings

The Application of Various DHTs in Early Cognitive Change

The Potential Application of Specific DHTs to Aid Those With Cognitive Complaints

Screening

Diagnostic Support

Intervention

Monitoring

Importance of the Caregiver’s Role

Limitations

Conclusions

Supplementary material

Abbreviations

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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