Smart Technology and Orthopaedic Surgery: Current Concepts Regarding the Impact of Smartphones and Wearable Technology on Our Patients and Practice

Abstract

Purpose of Review

While limited to case reports or small case series, emerging evidence advocates the inclusion of smartphone-interfacing mobile platforms and wearable technologies, consisting of internet-powered mobile and wearable devices that interface with smartphones, in the orthopaedic surgery practice. The purpose of this review is to investigate the relevance and impact of this technology in orthopaedic surgery.

Recent Findings

Smartphone-interfacing mobile platforms and wearable technologies are capable of improving the patients’ quality of life as well as the extent of their therapeutic engagement, while promoting the orthopaedic surgeons’ abilities and level of care. Offered advantages include improvements in diagnosis and examination, preoperative templating and planning, and intraoperative assistance, as well as postoperative monitoring and rehabilitation. Supplemental surgical exposure, through haptic feedback and realism of audio and video, may add another perspective to these innovations by simulating the operative environment and potentially adding a virtual tactile feature to the operator’s visual experience.

Summary

Although encouraging in the field of orthopaedic surgery, surgeons should be cautious when using smartphone-interfacing mobile platforms and wearable technologies, given the lack of a current academic governing board certification and clinical practice validation processes.

Introduction

Historically, orthopaedic decision-making relied solely on meticulous clinical evaluation and physical examination, limited to a few objective parameters for diagnosis and monitoring of treatment progression [1, 2]. Orthopaedic surgeons trusted intuition and experience in interpreting two-dimensional (2D) radiographic plain films to identify fracture patterns or pathologies, undertaking laborious manual radiographic measurement to develop pre-surgical plans [3]. In the operating room (OR), development of fine motor skills and steady hands came through repetition and intuition during arduous procedures, potentially predisposing surgeons to both physical and mental fatigue [4•].

Technological innovations have targeted many of these prior limitations, with improvements in telecommunication, data storage, and digitalization paving the way for significant change in how orthopaedic surgery and patient care could be delivered [5, 6]. More recent advancements have utilized secure data and telecommunication networks, while also incorporating use of embedded physical sensors, ultimately enabling complex and large-scale data exchange [7, 8]. In the past decade, these technologies have become centralized and often operated by internet-capable mobile devices; with over 80% of Americans reporting smartphone ownership in 2019, smartphones have become logical targets for medical innovation [8–10]. Smartphone ubiquity, combined with recent hardware and software advances, has led to the immersion of smart technology within medicine, enhancing our ability to diagnose, monitor, and treat patients’ conditions [11••]. Unlike expensive, highly regulated medical-grade equipment, smartphones and wearable technologies are affordable and accessible. They are always connected to the internet and establish two-way communication between patients and their respective physicians for disease management and tracking [8–10, 11••].

The following article will summarize current and anticipated trends of smart technology, defined herein as advances in internet-powered mobile and wearable technology that interface with smartphones, and their relevance in orthopaedic surgery. Specific focus is placed on implications of these innovations in improving diagnosis and examination, preoperative planning, intraoperative assistance, and postoperative rehabilitation and monitoring.

Diagnosis and Examination

Joint Range of Motion

Measuring joints’ range of motion (ROM) is a routine and vital component in assessing patients with musculoskeletal pathologies, providing baseline reference data for post-treatment comparison. Traditionally, ROM is assessed through visual estimation or goniometry, methods characterized by low interobserver reliability [12–15].

Principles of traditional goniometry have been applied to smartphone-based technology to potentially improve accuracy and perform testing without additional equipment. Many studies have evaluated smartphone use to measure spine [16–21], knee [22–27], finger [28–31], elbow [32, 33], hip [27], and shoulder [33–37] ROM. Two general methods have been commonly reported [17–37, 38••]. The first employs a phone-based inclinometer, where the phone is placed on the articulating limb during joint flexion/extension, with the ensuing difference between recorded angles reflecting the ROM. The second uses photographs of the joint in flexion and extension, from which both angle difference and respective ROM are calculated (Table 1) [17–38]. A recent systematic review evaluated reliability and validity data for smartphone applications, revealing high intra- and inter-observer reliabilities in most studies regardless of the joint, supporting this as a reliable potential replacement for traditional ROM measurement [38••]. However, this was mainly detected in relative correlation than absolute (mean difference and minimal detectable change) metrics, and in spinal rotation assessment compared to spinal extension and flexion.

Table 1.

Summary of articles using smartphone technology to assess joint range of motion (ROM)

Article	Study population	Joint	Method	Interface	Results
Ulluci et al. [16]	38 healthy subjects	Cervical spine	Clinometer application	iPhone Android	Excellent inter- and intra-phone/examiner reliabilities in measuring passive upper cervical ROM
Rodriguez-Sanz et al. [17]	25 patients with chronic cervical pain	Cervical spine	Clinometer and compass applications, as well as standard cervical ROM device	Android	Excellent intra-and inter-class reliabilities in all active ROMs except upper cervical spine flexion
Pourahmadi et al. [18]	30 healthy subjects	Lumbar spine	TiltMeter application and an inclinometer	iPhone	High intra- and inter-rater reliabilities in active lumbar flexion-extension ROM
Qiao et al. [19]	64 adolescents with idiopathic scoliosis	Thoracic and lumbar spine	Scoligauge application	iPhone	Excellent intra- and inter-observer reliabilities in measuring the axial trunk rotation
Balg et al. [20]	34 patients with idiopathic scoliosis	Thoracic spine	Scoligauge built-in accelerometer application and a scoliometer	iPhone	Excellent intra- and inter-observer reliabilities in measuring scoliosis-related rib hump deformity
Jacquot et al. [21]	20 patients with thoracic or lumbar kyphosis	Thoracic and lumbar spine	CobbMeter application and protractor	iPhone	Excellent intra- and inter-observer reliabilities in measuring spinal kyphotic angles
Castle et al. [22]	30 knee arthroplasty patients	Knee	DrGoniometer photo-based application and a standard goniometer	iPhone	High intra- and inter-rater reliabilities in measuring active knee ROM
Mehta et al. [23]	60 patients with knee osteoarthritis or total knee arthroplasty	Knee	i-Goni and standard goniometers	iPhone	Excellent intraclass reliability in measuring active knee ROM
Pereira et al. [24]	60 subjects (20 healthy; 20 acutely following knee surgery; 20 recently having knee surgery or trauma)	Knee	Accelerometer-based knee goniometer application and a standard goniometer	iPhone	In a single measurement, high intra- and inter-observer reliabilities in measuring active knee ROM
Milanese et al. [25]	6 healthy subjects	Knee	Accelerometer-based knee goniometer application and a standard goniometer	iPhone	Excellent intra- and inter-rater reliabilities in measuring active knee ROM
Dos Santos et al. [26]	34 healthy females with > 20° limitation of knee extension	Knee	ROM application	Android	Excellent inter-rater reliability in measuring active knee ROM
Hancock et al. [15]	3 healthy subjects	Knee	Goniometer Pro application, short- and long-arm goniometers, visual estimation, and Halo Digital Goniometer	iPhone	Excellent intra- and inter-rater reliabilities in measuring knee active ROM with no significant differences between the techniques used
Russo et al. [27]	10 fresh-frozen human cadavers	Hip and knee	Digital photography, visual estimation, and a standard goniometer	Computer-assisted infrared camera	Digital photography is comparable to other techniques in measuring passive hip flexion and internal/external rotation and knee flexion, but outperformed visual estimation and both modalities in measuring passive hip abduction and knee extension, respectively
Meals et al. [28]	15 subjects (8 with hand/wrist pathology; 7 healthy)	Wrist and hand	Digital photography and standard goniometer	Digital camera	High intra- and inter-rater reliabilities for hand/wrist active ROM measurements, but did not correlate with results from standard goniometry analysis except for wrist, ring finger proximal interphalangeal, as well as thumb metacarpophalangeal and interphalangeal flexions
Wagner et al. [29]	32 healthy subjects	Wrist	Digital photography and standard goniometer	iPhone	High inter-observer reliability as concordance between subjects and surgeons in measuring wrist active ROM
Zhao et al. [30]	50 patients with Dupuytrens’ contracture	Hand	Digital photography and standard goniometer	Not specified	Excellent interobserver reliability in measuring fingers active ROM
Lee at al. [31]	1 healthy subject	Hand	Goniometer, compass, and PT-Tools applications, as well as visual inspection and fluoroscopic-based standard goniometer	iPhone	Measurements retrieved from all three smartphone applications and visual estimation strongly correlated with standard fluoroscopic measurements, with high inter-observer reliability active finger flexion
Keijsers et al. [13]	40 subjects with or without elbow pathology	Elbow	Accelerometer-based joint goniometry application, digital photography, movie, and standard goniometer	iPhone	Both photography and movie showed at least good correlations with the standard goniometry, whereas the smartphone-based correlations good for elbow active pronation and supination, and weak and moderate for elbow active extension and flexion, respectively
Meislin et al. [32]	32 healthy subjects	Elbow	Digital photography and standard goniometer	iPhone	Excellent inter-observer reliability and concordance between subjects and surgeons in measuring elbow active ROM
Russo et al. [33]	10 fresh-frozen human cadavers	Shoulder and elbow	Digital photography, visual estimation, and a standard goniometer	Computer-assisted infrared camera	Precision of digital photography was higher than visual estimation and goniometry in measuring shoulder passive ROM, but higher than goniometry for elbow passive flexion measurements
Boissy et al. [34]	25 healthy subjects	Shoulder	Optotrak optical motion tracking system and iPod inclinometer	iPod	Digital inclinometer is highly accurate for active external rotation measurements of the shoulder, but not as much for shoulder flexion or abduction
Shin et al. [35]	41 patients with unilateral shoulder pathology	Shoulder	Clinometer-level and slope finder application and standard goniometer	Android	Excellent intra- and inter-observer reliabilities, except for internal rotation at 90° abduction in measuring shoulder active ROM
Mejia-Hernandez et al. [36]	75 patients with shoulder pathology	Shoulder	Inclinometer-based GetMyROM and photo-based DrGoniometer applications	iPhone	Excellent inter-observer reliability in measuring all passive and active shoulder ROM

The ease of use and sharing ability of these applications offer advantages; they may allow individuals to take measurements and share them remotely with their surgeons [11••]. Musculoskeletal pathologies could be screened and assessed, with cases warranting further care being identified and referred for further workup. This is especially true for ROM-related smartphone applications, which have not yet been fully implemented in the clinical setting [17–37, 38••]. This technology may be particularly beneficial when tailored to monitor physical therapy at home and track recovery progression as well as need for additional assistance [39]. However, as most of the aforementioned studies are limited to controlled settings and secure health privacy must be established, extensive investigation is warranted to better clarify the role of smartphone applications for remote diagnostics/evaluation.

Functional Motion Analysis

Monitoring of gait pattern and motion is essential to guiding management for disorders such as cerebral palsy [40], though it has wide applicability for musculoskeletal pathologies [41]. However, traditional gait/motion analysis requires expensive equipment, including 3D-capture cameras, highly specialized staff, and a controlled setting, limiting its access to institutions equipped with these factors [41].0

Wearable motion sensors offer the ability to assess temporal-spatial gait parameters in many settings [40, 42]. The Physilog 5 (Physilog, BioAGM, Switzerland) is a wearable foot-based inertial sensor that employs a 3D gyroscope, accelerometer, and barometer to measure movement. In children with cerebral palsy, Bregou Bourgeois and colleagues [40] demonstrated high accuracy and precision in stride length, speed, and strike, lift-off, and turning angles with this system. Given reported gait variabilities in children, these data substantiate the reliability and accuracy of such a system for measurement that may warrant further investigation in orthopaedic literature [42].

Patients with patellofemoral pain are commonly high-impact runners with maladaptive gait patterns. Retraining gait via feedback can be used to reduce both load and work completed by the knee, which subsequently may contribute to reduced pain [43, 44]. Wearables, such as the RunScribe (Scribe Labs, Half Moon Bay, CA), Garmin Forerunner (Garmin Inc., Olathe, KS), and zFlo Moticon Insole (zFlo Motion, Westbrook, ME), have been used to track maladaptive gait and improve gait training [45–50]. These devices use sensors for gait monitoring, and data generated is then sent to smartphone(s) to provide feedback for runners, with one study reporting reduced knee work by 26.9% at 30-day follow-up, with maintenance of this running pattern well after feedback was no longer provided [51]. When used during regular activity, this same strategy permitted runners to continue their normal routine [44].

Despite their potential benefits, a major limitation to wearable products stems from their inability to mitigate overuse injury [52]. Overuse injuries result from tibial load, yet many devices assess ground reaction force as a surrogate to tibial force, resulting in weak correlation between ground force and tibial load [52]. Additionally, these wearable systems may be limited by drifting of captured measurements from true measurements due to build-up of signal noise [53, 54]. Yet, the potential for continuous remote data capture in a manner that is convenient and user friendly warrants further evaluation of smart technology in aiding in functional monitoring following orthopaedic intervention.

Osteoarthritis Assessment

The Osteoarthritis Research Society International (OARSI) recommends monitoring hip or knee osteoarthritis via a series of functional tests to predict fall risk and monitor patients’ ability to complete their activities of daily living (ADLs) [55]. Core tests for monitoring this include a 30-s chair-stand, 40-m fast-paced walk, and stair-climb tests (Fig. 1) [55]. Smartphone-based functional assessments yielded similar results to monitored testing in clinic, with strong intraclass correlation for chair-stand and stair-climb tests (r ≥ 0.902) [56]. Moreover, mobile applications could enable remote longitudinal evaluation that do not require technique monitoring and save time [56].

Fig. 1.

A smartphone-based coordinated rendering of the position of a patient performing a 30-s chair-stand test (a); a 40-m fast-paced walk test (b); and a stair-climb test (c)

Teleprehabilitation

Prehabilitation has been shown to help reduce preoperative functional deterioration and need for postoperative rehabilitation, while also enabling earlier postoperative return to function [57, 58]. Yet, location, lack of transportation, and cost have been cited as barriers to participating in prehabilitation programs [59]. Chughtai-Shah et al. [60•] reported on a novel teleprehabilitation system (PreHab, PeerWell™, San Francisco, CA) that delivered exercises, dietary/nutritional counseling, and risk mitigation and pain management information prior to total knee arthroplasty (TKA), demonstrating that individuals using this system had shorter lengths of stay and reduced admissions to skilled nursing facilities; however, no improvements were observed in postoperative pain. Further studies evaluating the utility of telehealth platforms for prehabilitation are limited, supported by Shah and colleagues [61] reporting of underutilization of web-based health exercise programs in their evaluation of rehabilitation preferences of Arthroscopy Association of North America (AANA) members. Considering reduced postoperative admissions to rehabilitation facilities and lengths of stay, prehabilitation via telemedicine mobile platforms may offer orthopaedic surgeons and their patients a cost-effective and widely accessible tool to reach patients and potentially optimize their postoperative course [61–63].

Preoperative Planning

Radiographic digitalization has enabled the development of powerful filmless paperless preoperative planning tools [64, 65]. TraumaCad™ (Brainlab, Westchester, IL) is a computer-based platform for pre-templating, measurement, and planning. A mobile application was released and demonstrated at the American Academy of orthopaedic Surgeons (AAOS) 2015 Annual Meeting, transferring these capabilities to the palms of surgeons’ hands [66]. Steinberg et al. [67] reported accurate preoperative acetabular and femoral component selection within one size in 65/73 (89%) and 57/68 (87%) patients, respectively, when planning for total hip arthroplasty (THA). EndoMap (Siemens AG, Medical Solutions, Germany), another templating software, has yielded similar correct predictions within one component size: femoral components in 26/36 (72%) patients and acetabular components in 31/36 patients (86%) [68]. While conventional templating with physical radiographs has yielded similar findings, digital templating is associated with reduced radiation exposure, fewer unsatisfactory films, and lower costs [69]. Such software may help improve workflow and time spent performing preoperative planning, while also enabling this to be done remotely.

Preoperative surgical planning in spine surgery has embraced the use of dedicated spine software within the last decade, offering accurate diagnosis and treatment-planning tools, enabling simultaneous assessment of multiple parameters and prediction of changes in postoperative sagittal alignment [70]. However, use of these tools still requires time, from a few minutes for 2D analysis to up to 20 min for complex 3D reconstructions [71–73]. Computer-assisted artificial intelligence and machine learning algorithms (MLAs) are currently being developed and tested in spine research with promising potential, from anatomic localization to predictive analytics and clinical decision support [4, 74]. Yet these tools are far from smartphone/mobile integration. While assessment of spine ROM predominates the role of smartphones in preoperative assessment for spine surgery, Lee and colleagues [75] recently demonstrated comparability and reliability between a smartphone application and PACS-based measurements for sagittal balance parameters (lumbar lordosis, pelvic incidence, sacral slope, and pelvic tilt), with a significant reduction in time required for measurements via smartphone. Comparisons between such applications and gold-standard dedicated spine software are lacking [75], yet such studies represent the next step in assessing utility of smartphones in improving workflow and time spent toward planning spine surgery.

Intraoperative Assistance

Surgical Navigation and Assistance

Robotic-assisted and computer-based surgical navigation systems have been designed to increase precision of implant placement [76]. Recent work has focused on transferring principles used by these technologies to smartphones [77]. Multiple groups have demonstrated positive clinical results with smartphone-mediated acetabular cup positioning, placing the phone parallel to the cup holder and using the on-screen angle to guide acetabular component placement [78, 79•]. In a recent analysis, 15 orthopaedic surgeons placed an acetabular cup in a pelvis model using a smartphone-based application with 100% of attempts at various angles falling within the Lewinnek safe zone [80]. When tested in patients, a mechanical alignment guide combined with a level indicator smartphone application achieved promising results in 37/41 (90.2%) patients undergoing THA, compared to only 23/41 (56.1%) patients via conventional technique [79•].

Zamani and colleagues [81] outfitted existing surgical instruments, including power drills and saws, with sensors and haptic technology to design “smart” tools. Though they sought to assess the surgical training skills of orthopaedic residents before and after a motor skills course, these instrument modifications provided tactile kinetic and kinematic feedback that could be integrated and relayed to mobile platforms to generate feedback reports for surgeons, potentially assisting in improving surgical decision-making [81, 82].

Augmented Reality

Smartphones are also being combined with surgical navigation systems, making use of their hardware to assist in intraoperative implant placement by creating simulated visualization of maneuvers, offering surgeons accurate navigation/visualization without radiation exposure [77, 83]. Ma et al. [83] proposed an augmented reality (AR) navigation system that combines optical and electromagnetic tracking systems with 3D image overlay, generating renderings of skeletal positioning to guide distal interlocking screw placement in intramedullary tibial nails, yielding 100% accuracy during AR-guided drilling. AR-HIP is a mobile application developed by Ogawa et al. [77] that applies optic tracking and 3D positioning to improve implant placement, superimposing acetabular cup and placement angle images in the surgical field, all viewed on a smartphone (Fig. 2). When comparing the difference in intraoperative acetabular placement angle and angle measured on postoperative computed tomography (CT) scan between AR-HIP and goniometry, AR-HIP was significantly more accurate than intraoperative goniometry for radiographic anteversion (2.7° vs. 6.8°), with no difference in radiographic inclination between AR-HIP and goniometry (2.1° vs. 2.6°) [77].

Fig. 2.

Depiction of smartphone-based optic tracking and 3D positioning using the AR-HIP mobile application. The system uses a pelvic computed tomography (CT) scan to render a 3D coordinate system, which is then marked on the operative field using stainless guides placed on the skin. The smartphone is placed on an acetabular cup holder, which uses the camera to position itself relative to the guides

Smart Glasses

Intraoperative fluoroscopy is frequently utilized and preferred for visualization of bone and instrumentation placement, despite known associated risks with emitted radiation exposure [84, 85]. Surgeons must look away from the surgical field to view images taken, and this can lead to increased surgical time and radiation exposure [86•]. Smart glasses, such as Google Glass (Google Inc., Mountain View, CA) and PicoLinker (Westunitis Co., Japan), offer surgeons the ability to maintain gaze and focus on the operative field while simultaneously viewing fluoroscopic or preoperative radiographs in their peripheral visual field (Fig. 3). This offers potential for improved accuracy and reduction in radiation exposure dosage and time as well as total operative time [86•, 87–89]. Chimenti and Mitten [89] demonstrated how use of Google Glass to view fluoroscopic imaging, when compared to standard fluoroscopic visualization, required fewer images during percutaneous hand fracture fixation (3.6 vs. 6.4).

Fig. 3.

Depiction of a surgeon’s field of view utilizing smart glasses, allowing for visualization of fluoroscopic imaging without redirecting the line of sight from the operative field

Smart Implants

Naturally, while the environment and equipment utilized in the OR are logical targets for innovation, implants themselves represent robust potential vehicles for data collection and communication with smart devices, especially with evolution of sensor and wireless communication technology [90, 91, 92••]. Smart orthopaedic implants have been utilized to measure physical parameters, including strain, force, pressure, displacement, balance, temperature, and proximity [91–94]. Direct applications are reported in THA/TKA, spinal fusion, and fracture fixation, while significant published data demonstrate potential applications in the hip, knee, shoulder, spine, bone, and cartilage [91, 92••]. To date, smart hip and knee joint implant applications have predominantly been academic in nature and have not been evaluated clinically [91, 92••], though research has demonstrated their utility in verifying in vivo implant loading and performance, guiding surgical technique and postoperative rehabilitation, and detecting prosthesis loosening [91, 92••, 95, 96]. Smart spine implants, which include fixating rods, interbody implants, and vertebral body replacements, have provided valuable insight into static and dynamic biomechanical forces about the spine, while also delivering important data on the biomechanical role of posture, activity, and muscle activation. Recently, research has demonstrated the potential of smart implants to objectively and quantitatively assess progression of spinal fusion [92••]. Fracture fixation is an area where smart implant data is guiding clinical decision-making, assisting in weight-bearing modification to guide mobilization in accordance with plate endurance and prevent mechanical plate failure [92••, 97].

Barriers to clinical incorporation of smart implants have generally included power consumption, robustness, implant/sensor size and cost, range of communication, and data transfer rates, the latter of which currently impedes their integration with smartphone technology [91, 92••]. Yet, with vast degrees of progress being made in implantable sensor and wireless communication technology, it is not unreasonable to recommend future investigation to focus on clinical application of smart implants and how integration of mobile platforms can optimize these [92••, 95].

Postoperative Monitoring

Automated Doctor-Patient Communication

The capability of smartphones to deliver automated instant messaging has enabled concurrent tracking of patients’ pain, medication use, and recovery [98]. Smartphones have been validated for use with standardized questionnaires to assess pain, quality of life, and ability to accomplish ADLs [99–101]. Instant messaging has demonstrable efficacy in providing patients with information concerning surgery and recovery [102, 103]. Premkumar and colleagues [98] reported a 96.1% response rate following joint and spine surgery when utilizing a smartphone text-messaging-based survey of pain and opioid use, compared to a 66.6% response rate with automated postoperative emails. Tracking postoperative opioid use can also be successfully conducted using automated messages [100, 103, 104]. These results demonstrate the potential application of automated communication toward developing strategies to reduce postoperative opioid use.

Patient information, including laboratory and imaging results, can be quickly shared between physicians using instant messaging. Up to 80% of attending physicians use text messages to share deidentified, HIPAA-validated information without being physically present in a hospital [105]. Physicians can also now view radiographs, assess patients, and create therapeutic plans on-the-go using instant messaging and mobile phones [106–109]. Gulacti et al. [106] demonstrated that when emergency physicians sent history, vitals, physical exam findings, and imaging to orthopaedic specialists via encrypted smartphone messaging (WhatsApp Messenger, WhatsApp Inc., Facebook, Mountain View, CA), they responded, on average, within 4.9 min. CT, X-rays, and magnetic resonance imaging (MRI) can all be used to diagnose fractures and dislocations on a mobile screen without image quality loss [107–109]. Yet currently, this modality requires longer time to load and read images, with a mean difference of 3.98 min between reads using an iPhone (Apple Inc., Cupertino, CA) and computer workstation [109]. Physicians in resource-limited hospitals that lack full-time, in-house orthopaedic services may be able to address these gaps using some of these solutions; however, issues with data transfer and latency are challenges that need to be addressed prior to widespread adaptation [107, 110].

Postoperative Rehabilitation

Smart technology-based postoperative rehabilitation and monitoring in orthopaedic surgery involves wearable motion sensors or smartphones to monitor limb motion, and this may require training of patients to perform exercises or interventions. In some cases, data is relayed to software, and patients are given real-time feedback on exercise technique, with additional focus placed on difficulty experienced as well as pain levels [111]. Chughtai et al. [112] demonstrated how an app-controlled home-based remote neuromuscular electrical stimulation (NMES) device allowed patients to self-manage muscle strengthening and ROM improvement, potentially increasing treatment adherence, while also providing real-time monitoring to their physicians following TKA. Remote monitoring can improve patient independence, reduce the need for constant physical therapy sessions, and lead to improved patient adherence, pain, and strength [113].

Connected rehabilitation programs have numerous benefits, mainly as a result of patient motivation to adhere to scheduled exercises in 79–90.4% of cases [114, 115]. Compared to the traditional patient adherence rate of 67%, these results highlight the effectiveness of such programs for both patients and clinicians [116]. Mobile phone–based telerehabilitation systems have been shown to be effective in establishing self-managed postoperative rehabilitation in patients following lumbar spinal surgery, while also yielding better patient-reported outcome measures (PROMs) [117]. However, technical difficulties (application learning, crashing, and customization) should be accounted for, as they may demotivate patients and hamper engagement during strenuous exercise or unhelpful feedback perception [115].

More recent work has focused on the integration of sensor-based systems in postoperative telerehabilitation. Naeemabadi and colleagues [118] developed a telerehabilitation system, with a portable sensor-based patient platform and web-based platform for healthcare providers, with high acceptance levels among users in preliminary evaluation following knee surgery. Bell et al. [119] more recently developed a remote rehabilitation monitoring system, combining two wireless inertial measurement units (IMUs) with an interactive application for patients and web-based portal for clinicians. They found good-to-moderate agreement between IMU-based knee goniometry and video-based motion tracking systems for all tested exercises, with accuracy within 3° [119]. Ramkumar and colleagues [120] recently advanced sensor-based patient monitoring in their report of a wearable and MLA-based remote patient monitoring (RPM) platform, with continuous, uninterrupted data collection from wearable knee sleeves paired with a smartphone application at baseline prior to TKA. Their study found patients to be both motivated and engaged with the system; the interactive application, where patients could report postoperative opioid usage and PROMs and physicians could monitor HEP compliance and physical/functional progression, with MLA-based complete data capture may represent the future of postoperative patient monitoring following orthopaedic procedures [120].

Future Directions

With the increasing orthopaedic evidence as well as complexity of procedures and evolution of surgical technology, all combined with limited time availability, surgical simulation represents a mechanism by which supplemental exposure to techniques and procedures may be obtained [121]. Virtual reality (VR) systems that simulate the environment can be used as such, and though many currently lack haptic feedback and realism of audio and video, development and integration of smart tools, as evidenced by Zamani and colleagues [81], may represent a plausible solution [81, 122]. The Microsoft HoloLens (Microsoft, Redmond, WA) has been combined with 3D-printed bone to develop a patient-specific model for immersive surgical simulation; increasing realism with sound integration superimposes virtual images onto the surrounding environment [123, 124]. Fundamental Surgery (FundamentalVR, London, England) is another surgical simulation software that utilizes a VR headset combined with video-gaming joysticks and haptic feedback to simulate several operative interventions, including spinal fusion, hip arthroplasty, and knee arthroplasty [125, 126]. PrecisionOS (PrecisionOS, Vancouver, Canada), also a VR-based program, extends the simulation experience by recreating specific fractures in an OR setting and objectively assessing the operators’ surgical precision using established metrics while providing the user with play-by-play feedback in their display [127]. The DEXMO (DextaRobotics, Shenzen, China) includes a pair of gloves embedded with motors and sensors that enable users to virtually touch and feel objects. It may have implications in the surgical simulation educational field, in that it can add a tactile aspect to the operator’s visual experience [124, 128]. While the company has also created a simulated, interactive OR, current evidence supporting any utility of this modality over others is not available, and additional comparative studies are warranted. Additionally, these technologies lack mobile platform integration, limiting the extent of their utility to institutions with both the resources and space to accommodate such equipment.

Conclusion

Smartphone-interfacing mobile platforms and wearable technologies are promising tools with the potential to improve the lives of patients and engage them in their treatment, while augmenting the abilities and level of care that orthopaedic surgeons may provide. A summary of recommendations for the application of mobile and wearable technology interfacing with smartphones in the clinical orthopaedic setting can be found in Table 2. Given the lack of certification by an academic governing board and validation in clinical practice, surgeons should remain cautious when exploring implementation of such new technologies. The use of these platforms could also cause a surgeon or trainee to lose valuable hands-on experience and may negate additional input gained from human senses, ultimately resulting in a loss of deductive and inductive reasoning ability. While the future that smart technology offers to the field of orthopaedic surgery is encouraging, further studies that compare this innovation to standard techniques familiar to the user are warranted.

Table 2.

Recommendations for care

Grades of recommendations for the application of mobile and wearable technology interfacing with smartphones in the clinical orthopaedic setting*
Joint range of motion can be measured using the inclinometer or camera of a smartphone [12–38].	A
Wearable motion sensors can be employed to provide feedback to modify gait in patients with patellofemoral pain [43, 44].	B
Smartphone-guided acetabular cup placement effective and precise when compared to conventional technique [78–80].	B
Augmented reality (AR)–guided navigation offers surgeons with the ability to improve implant placement and intraoperative goniometry [77, 83].	B
Smart glasses can be effectively used to provide fluoroscopic imaging visualization without redirecting one’s line of sight from the surgical field [86, 87, 89].	B
Automated doctor–patient messaging can be used to effectively monitor and communicate with patients postoperatively [98–104].	B
Instant messaging is an effective method of physician-to-physician communication, including the review of radiological images [105–110].	B
Web-based prehabilitation and postoperative rehabilitation programs can positively impact patient satisfaction and objective postoperative outcomes [60, 61].	B
Preoperative surgical planning software suites with mobile phone capabilities offer surgeons the ability to:
• Predict the component size in total hip arthroplasty between 72 and 89% of the time within one size and offer reduced radiation exposure and cost [67–69].	B
• Reliably measure sagittal balance parameters of the spine with reduced time required to do so when compared to PACS-based measurements [75].	C
Smart technology can be successfully deployed for self-monitored postoperative rehabilitation [111–120].	C
Smart implants show great promise but lack substantial clinical investigation and application [90–97].	I
According to Wright [129], grade A indicates good evidence (level-I studies with consistent findings) for or against recommending intervention; grade B, fair evidence (level-II or III studies with consistent findings) for or against recommending intervention; grade C, poor-quality evidence (level-IV or V studies with consistent findings) for or against recommending intervention; and grade I, insufficient or conflicting evidence not allowing a recommendation for or against intervention.

Data availability

Not applicable.

Declarations

Conflict of Interest

Not applicable.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.