Abstract
ABSTRACT
Introduction
Rare diseases (RDs) affect millions of people worldwide and present major challenges for research due to small patient populations, limited longitudinal data and the difficulty of capturing real-world disease manifestations. Digital technologies provide new opportunities to collect multimodal data directly from patients and their environments. In particular, video recordings, wearable-based physical activity monitoring and digital questionnaires can generate detailed, longitudinal information on symptoms, functional abilities and daily-life impact. The digital tools for rare disorders (DT4RD) protocol aims to develop and evaluate a digital framework that integrates these technologies to support data collection and analysis in RD research.
Methods and analysis
DT4RD will implement a technology-driven platform designed to collect and analyse multimodal patient-generated data. The protocol includes three main components: (1) structured video capture to document clinical signs and functional performance, enabling remote assessment and computational analysis; (2) continuous physical activity monitoring using wearable sensors to quantify mobility and daily activity patterns and (3) digital questionnaires to capture patient-reported outcomes and contextual information. These data streams will be integrated within a dedicated digital infrastructure supporting secure data collection, storage and analysis. This pilot study will be conducted with participants affected by rare neuromuscular diseases to evaluate the feasibility, usability and analytical potential of the platform as well as its ability to generate clinically relevant insights from multimodal digital data anchored to regular hospital visits.
Ethics and dissemination
The study was approved in France by the Comité de Protection des Personnes Sud-Est III on 21 February 2023 (National Number ID-RCB 2022-A02749-34). UK approval was granted by the Health Research Authority and Health and Care Research Wales on 4 March 2024 (IRAS project ID 331474). The protocol has been registered on ClinicalTrials.gov under the number NCT05798325. All participants will be provided with verbal and written information about the study and its procedures before providing written informed consent. Data will be anonymised and handled in accordance with GDPR, French CNIL regulations (MR-001) and applicable national data-protection requirements. Results will be communicated through peer-reviewed publications, conference presentations and lay reports.
Trial registration number
Keywords: Clinical Trial, Digital Technology, eHealth, Neuromuscular disease, Patient Reported Outcome Measures, Wearable Devices
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This longitudinal, multicentre, observational protocol includes hospital assessments at baseline, 6 months and 12 months, with home-based digital monitoring between visits.
Hospital-based clinical assessments include timed walking tests, motor function scales, strength testing, range of motion assessment and optional spirometry.
Home-based digital measures include wearable-based activity monitoring, links sensor system goniometry, standardised video-recorded motor tasks, digital questionnaires and optional spirometry.
Home-based digital measures are anchored to scheduled hospital visits to support comparison between home-based and hospital-based assessments.
As a feasibility study, the protocol will primarily assess data recovery, usability and consistency across modalities and is not powered to assess clinical effectiveness.
Background
Digital technologies, including wearables, sensors, video-based assessments and electronic questionnaires, can enrich established Clinical Outcome Assessments, Clinician-reported Outcomes, Performance Outcomes and patient-reported outcomes (PRO) by enabling repeated assessment outside the hospital setting. In neuromuscular diseases, such tools may capture aspects of mobility, fatigue, sleep, respiratory function and daily activity that are only partially reflected by intermittent site-based evaluations. Their value, however, depends on clinical relevance, patient acceptability, data quality and validation against established measures. For this reason, digital tools should be selected according to the clinical domains they are intended to measure and co-designed with patients and advocacy groups to minimise burden and maximise usability.
Real-world data (RWD) and Real-world evidence are increasingly used to complement traditional clinical trial evidence, including by informing trial feasibility and design, supporting pragmatic or hybrid trial designs and providing longitudinal information from routine-care or home-based settings.1 This paradigm may improve recruitment, retention, convenience, autonomy, diversity and generalisability, while reducing the need for repeated hospital visits.2 3 Their implementation has been facilitated by connected devices, wearable sensors, mobile health applications and evolving regulatory guidance supporting decentralised elements in clinical research.4 5 Clinical sites nevertheless remain essential for recruitment, clinical characterisation, safety oversight and anchoring of remote measures to established assessments.6
Digital medicine can only be integrated into clinical research and practice if the measures used are reliable, clinically valid and interpretable. Some digital measures are already established in clinical contexts, including ambulatory arrhythmia monitoring,7 step-count tracking8 and fall detection systems.9 In neuromuscular diseases, home pulmonary monitoring has shown feasibility and clinical value in Duchenne muscular dystrophy (DMD),10 and stride velocity 95th centile (SV95C) was the first wearable-derived digital endpoint to receive European Medicines Agency qualification for quantifying ambulation in ambulant boys with DMD aged ≥5 years.11 12 Additional wearable-derived endpoints are also emerging, including the 6-min Activity-95th Centile in DMD.13 These data support the evaluation of multimodal digital tools in rare neuromuscular disorders, provided that their feasibility, data recovery, validity and relationship with conventional clinical assessments are tested systematically.
The digital tools for rare disorders (DT4RD) project aims to establish a proof of concept for non-invasive remote tools that assess mobility during daily living in patients with rare neuromuscular diseases. The project will evaluate the feasibility of using these tools and explore the relationship between home-based digital measures and conventional clinical assessments obtained in hospital settings. Although mobility is the primary focus, the DT4RD toolbox also includes related functional and clinical domains that may influence or contextualise mobility, including muscle strength, range of motion, fatigue, pulmonary and cardiac function, pain, balance, dexterity, ataxia, falls, tremor and user acceptability (putative and non-exhaustive list). The digital tools specifically selected for DT4RD were chosen to capture complementary domains of neuromuscular disease in daily life. Wearable activity monitoring provides continuous information on mobility, activity level, cardiorespiratory parameters and sleep; electronic goniometry enables repeated quantification of joint movement during usual activities; video-recorded tasks allow remote observation of clinically meaningful motor functions; home spirometry captures respiratory involvement in participants for whom this is clinically relevant and electronic questionnaires document patient-reported symptoms, experience and contextual information. Together, these modalities provide a multimodal assessment framework designed to compare home-based digital measures with conventional hospital-based evaluations while limiting participant burden.
Organising a decentralized clinical trial (DCT) presents several technological challenges, particularly around connectivity, inter-operability and integration of digital tools.14 Participants may use different devices, operating systems and internet environments, creating variability in connectivity that can lead to data delays or missing information. Multiple platforms must inter-operate seamlessly, which often requires harmonising data formats, ensuring secure application programming interfaces and maintaining consistent performance across vendors. Effective integration of these technologies is essential for real-time monitoring, reliable data flow and coordinated trial operations. Without robust connectivity, strong inter-operability frameworks and tight system integration, the feasibility and scientific integrity of a DCT can be compromised. Regulatory challenges also arise in DCTs, as sponsors must navigate varying regional requirements for remote consent, data privacy, telemedicine practices and the validation of digital health technologies, all of which can complicate trial design and implementation.15 Secure data storage is another critical issue, as DCTs generate large volumes of sensitive information that must be anonymised, stored in compliant environments and managed in accordance with diverse regional data-protection regulations.
The key objectives of the DT4RD project are:
To compare hospital-based clinical assessments with data recorded remotely.
To evaluate how sensor-based technologies can enhance measurement accuracy both at home and during clinical visits.
To promote user-centred design and seamless technology integration.
To assess reliability and validity, ensuring comparability of common measures assessing similar constructs.
To demonstrate a proof-of-concept framework that enables interoperability and interchangeability across digital measures.
Hypothesis
We hypothesise that measurements at home are feasible and operative and may be complementary and consistent with hospital-based clinical assessments owing to the fact that they are more frequent, less tiresome and stressful for the patients and more related to real-life situations.
Primary objective
To assess the feasibility of remote assessments of mobility and functional capacity in patients with neuromuscular disorders, using data recovery rate from the different acquisition modalities as the primary feasibility outcome.
Secondary objectives
To assess the repeatability, consistency and technical robustness of home-based digital measures.
To anchor home-based digital measures to hospital-based clinical assessments of related functional domains.
To establish the infrastructure required for decentralised clinical trial execution.
To evaluate user experience and engagement with the digital tools.
Description of the consortium
The DT4RD consortium brings together clinical, technological and patient-advocacy expertise required to develop and evaluate remote digital monitoring tools in rare neuromuscular diseases. Aparito provides the Atom5 platform, which supports electronic questionnaires, video recordings and data transfer to the clinical portal. In this study, PROs refer to health information reported directly by participants, whereas patient-reported outcome measures (PROMs) refer to the electronic questionnaires used to collect these data. Yumen Bionics provides the links sensor system for wearable sensor-based movement assessment. The Institute of Myology and the John Walton Muscular Dystrophy Research Centre are responsible for clinical implementation, participant recruitment, hospital-based clinical assessments and interpretation of the digital measures in relation to neuromuscular disease. Metabolic Support contributes to patient and public involvement, including input on participant acceptability, communication and dissemination. Together, these partners provide the infrastructure required to assess the feasibility, validation and application of home-based digital measures anchored to hospital-based clinical assessments.
Methods and analysis
Detailed descriptions of each measurement, both at the hospital and at home, are provided as an online supplemental document. The main procedures are summarised below.
Study design
This is a longitudinal, multicentre, observational study aiming to enrol 40 patients aged 12 to 60 years. Participants will be followed for 12 months, with visits at the hospital at baseline, 6 months and 12 months. In parallel, continuous and periodic data collection will occur at home using digital devices.
No formal power calculation was performed, as this is a feasibility study and is not designed to test clinical effectiveness or disease-specific efficacy endpoints. The planned sample size of 40 participants was chosen pragmatically to provide sufficient information on recruitment, adherence, data recovery and usability across the two participating clinical sites, while remaining feasible for a 12-month longitudinal study in a rare neuromuscular disease population. This sample size is expected to provide adequate precision to estimate the primary feasibility outcome, the data recovery rate and to explore consistency between hospital-based and home-based measures.
Inclusion criteria
Aged between 12 and 60 years.
Patients with a genetically confirmed/molecular-proven neuromuscular disorder.
Patients experiencing walking difficulties in the home and at high risk of limiting social participation and walking outside of the home.
Written informed consent.
Able and willing to comply with all protocol requirements, including video recording.
Affiliated to or beneficiary of a social security scheme.
Non-inclusion criteria
Patient walking 10 metres in less than 10 s.
Guardianship/trusteeship.
Pregnant or nursing women.
Patients having relevant concomitant pathologies that, in the appreciation of the investigator, could interfere with protocol compliance.
Recruitment of participants
Participants will be recruited from patients followed at the Institute of Myology and the John Walton Muscular Dystrophy Research Centre. Eligible patients will be approached by the investigating team and provided with verbal and written information about the study. Written informed consent will be obtained before any study-specific procedures, in accordance with the ethics-approved protocols: Comité de Protection des Personnes Sud-Est III for France and Health Research Authority and Health and Care Research Wales approval for the UK.
Risk-benefit balance
No short, medium or long-term benefits are expected for the patients participating in this study. This study will, however, validate a new paradigm in patient evaluation, which could benefit future patients. Potential side effects could be fatigue and muscle pain induced by the performance of evaluations. The major risk of these evaluations is mainly related to the risk of falling during the 10-meter walk test (10mWT) and the 2-min walk test (2MWT). To minimise the risks, all the evaluations performed onsite will be performed under the close supervision of a certified physiotherapist (PT).
All devices used in this study (except for the Garmin vívosmart 5) have been developed according to general and specific standards for medical devices. The Garmin vívosmart 5 is a commercial device compliant with European regulations regarding electronic devices.
Visits at the hospital
Each patient will attend three site visits on which home assessments will be anchored (figure 1). The duration of this hospital visit is about 3 hours and 30 min. The patients will come every 6 months over the period of 12 months (ie, three hospital visits). Each visit will include the following evaluations:
Figure 1. Assessments at the hospital and at home. The duration of follow-up will last a full year. 10mWT, 10-metre walk test; 2MWT, 2-min walk test; MFM, motor function measure; NSAA, North Star Ambulatory Assessment; NSAD, North Star Assessment for Limb-Girdle-Type Muscular Dystrophies; PUL, performance of upper limb; TANS, Transition Assessment North Star.
10mWT (spontaneous and fast gait speed).
2MWT.
32-item motor function measure (MFM32).
Performance of upper limb (PUL).
Strength (knee extension, grip and pinch).
Spirometry evaluation (forced vital capacity (FVC), peak expiratory flow, forced expiratory volume in 1 s (FEV1)) in a sitting position (optional, see below).
Range of motion evaluation (goniometry).
In addition, patients with DMD or a limb-girdle-type muscular dystrophy will be asked to perform a North Star Ambulatory Assessment (NSAA) or North Star Assessment for Limb-Girdle-Type Muscular Dystrophies (NSADs), respectively. Patients with another neuromuscular disorder will be asked to perform the Transition Assessment North Star (TANS) scale.
To set up the links sensor system goniometers that will be worn at home (and during 10mWT and 2MWT during the onsite visits), morphometric measurements (distance between shoulder–elbow–wrist and between hip–knee–ankle (lateral malleolus) – floor) will be collected at the inclusion visit and for growing patients, also 6- and 12-months later.
At the last visit, the patients will also be asked to answer a specific patient reported experience measures (PREM) questionnaire (see online supplemental material).
Home-monitoring
To ensure that the data from the recordings that will be made at the patient’s home can be compared with the data obtained during the patient’s first visit (baseline), the participant will be given instructions on how to use the wearables, that is, the Garmin Vivosmart 5 and the Links Sensor System, as well as the Atom5 for video recording and answering PROMs and questionnaires.
The data recovered during the home measurements (Garmin smartwatch, links sensor system, PROMs, video recordings) will be uploaded onto Aparito’s secure server and visualised in the clinical portal (figure 2). Study participants will download the study-specific patient-facing app on their own smartphone (compatible with both iOS and Android) once they provide informed consent for their participation in the study. Through the app, patients complete PROMs and video recordings which are transferred to the clinical portal in real time, as well as links sensor system data, while Garmin data is automatically synchronised (near real-time) when the patient opens the app.
Figure 2. DT4RD framework for home monitoring. DT4RD, digital tools for rare disorders; PREMs, patient-reported experience measures; PROMs, patient-reported outcome measures.
If a study participant is identified as not having a suitable smartphone (eg, lacking Bluetooth and video recording capabilities), a smartphone with Wi-Fi connectivity will be provided for the duration of participation in the study.
At home, the patient will be asked to wear an elbow and a knee electronic links sensor system goniometer on the dominant side (writing hand) every 2 weeks for 3 days: 2 week days and 1 weekend day chosen by the patient but consistent throughout the duration of participation in the study (eg, every Tuesday, Thursday and Saturday) during waking hours. These devices will record the accelerations and rotation speed of both joints. The devices should be worn on the same side throughout study participation. Data collected through the sensor will be directly transmitted through the Atom5 platform to a secured server.
Once every 4 weeks, and during one of the 3 days that the patient will be wearing the goniometer (Saturday, for instance), the recording of the joint movement will be synchronised with video measurements: The patients will be offered to perform standardised motor tasks for the upper limbs (hands-to-head), the lower limbs (sit to stand) and a self-chosen task that is important to them. These tasks will be video recorded using the Atom5 app, with the assistance of a family member or a provided tripod. The patient will receive a reminder through the application before each test session. If video data is not received at the clinician dashboard, an email notification will be sent to the study staff to follow-up with the patient.
Every 4 weeks, patients who received a Spirobank Smart spirometer (only patients with significant clinical respiratory impairment) will be asked to perform a pulmonary function test using this device and its dedicated phone app (MIR Spirobank). This test is performed in a sitting position. The patient can ask a caregiver to help them in maintaining the device in the correct position during the test. The patient will perform three attempts of FVC following the instructions (Spirobank user manual), and the best attempt will be automatically saved on the application. During visits two and three, the study coordinator will transfer the spirometry reports through the Spirobank app directly to the electronic case report form, including FVC, peak expiratory flow (PEF) and FEV1.
Throughout the whole time the participant is taking part in the study, the patients will also wear the smartwatch (Garmin vívosmart 5). This watch contains various accelerometers and sensors which will allow the recording of the overall activity of the patient as well as the monitoring of different parameters during day and nighttime:
Cardiorespiratory parameters (heart frequency, beat-to-beat intervals, respiratory rate, oxygen saturation).
Physical activity (type, duration and intensity, step count, distance).
Sleep quality.
Electronic questionnaires and e-diaries will be administered through the Atom5 app to collect PROs, patient experience and contextual information relevant to the interpretation of the digital measures. These data-collection materials are described in the supplementary material and include quality-of-life questionnaires, the Quality of Life in genetic Neuromuscular Disease questionnaire for participants aged over 16 years, the EQ-5D-Y for younger participants, the ACTIVLIM questionnaire, the Fatigue Severity Scale, the short version of the International Physical Activity Questionnaire, the modified Short-form McGill Pain Questionnaire, fall diaries, event diaries for factors affecting mobility, sleep diaries and the PREM questionnaire administered near the end of follow-up.
During this study, the collection of a large part of the data will be partly dependent on the patient’s compliance, on their engagement with the devices and tools (goniometer, smartphone application, etc.), as well as any technical issues that may arise. Electronic notifications will be sent to participants as reminders to complete the video tasks and e-questionnaires, including reminders to synchronise the wearable and sensor devices. The study coordinator will phone the patient within 1 week after the visit to provide support regarding wearable use, video recording or other issues that might prevent the correct collection of data from home. Study staff will also receive alerts when no engagement with the platform is detected or when no data are received in the clinician dashboard.
Statistical analysis
Statistical analysis will be performed on all data pooled from the two investigation sites (Institute of Myology, Paris and the JWMDRC, Newcastle). Statistical analysis will be blinded to avoid site-specific biases. Standard statistical methods of descriptive statistics will be used to describe the characteristics of the study cohort at different time points. The assumptions of normality and sphericity will be checked when appropriate. Descriptive and inferential analyses will compare home and hospital data. Repeated measures ANOVA will evaluate changes across timepoints. Mixed models and correlation tests will assess data consistency across modalities.
One-year follow-up analysis
A one-way repeated measures ANOVA will be used to analyse the evolution of the variables measured three times (0, 6, 12 months’ time points) at the hospital over 1 year of follow-up.
A regression model will be used to analyse the evolution of the variables measured at home over 1 year of continuous monitoring every day (Garmin vívosmart 5), every 2 weeks (wearable Links Sensor System goniometers) or every month (video-recorded tasks, spirometry, questionnaires).
Predefined hospital-based and corresponding home-based measures are summarised in table 1. For variables measuring the same construct at home and in hospital, such as FVC, PEF and FEV1, home measurements closest to each hospital visit will be compared with hospital measurements using two-way repeated-measures ANOVA, with timepoint and setting as factors. Longitudinal analyses incorporating all available home measurements will additionally be performed using linear mixed models.
Table 1. DT4RD predefined hospital- and home-based comparator measures.
| Clinical domain | Hospital-based measurement | Predefined corresponding home-based measurement | Variable type / construct | Planned comparison category |
|---|---|---|---|---|
| Respiratory function | FVC, PEF and FEV1 measured by hospital spirometry in a sitting position. | FVC, PEF and FEV1 measured using the home Spirobank Smart spirometry, using the best of three attempts. | Continuous; same construct | Matched home-hospital comparison at visit timepoints; longitudinal mixed model using all available home values. |
| Lower-limb function/sit-to-stand | NSAA item 3, TANS item 6, MFM item 24 or NSAD item 8, depending on diagnosis and scale administered. | Sit-to-stand task recorded at home using the Atom5 app; derived variables may include score and/or completion time. | Categorical and/or continuous; related construct | χ2 for categorical variables; one-way ANOVA for continuous home measures across hospital score levels; repeated-measures correlation if both variables are continuous. |
| Upper-limb function | PUL2 entry item and/or MFM item 15. | Hands-to-head task recorded at home using the Atom5 app; derived variables may include movement surface, completion performance or task score. | Categorical and/or continuous; related construct | χ2, one-way ANOVA or repeated-measures correlation according to the derived variable type. |
| Global motor function/activity limitation | Total MFM32 score. | ACTIVLIM score collected at home through the digital questionnaire platform. | Continuous or ordinal score; related construct | Repeated-measures correlation between hospital motor function and home-reported activity limitation. |
| Muscle strength | Knee extension strength. | Sit-to-stand time derived from home video recording. | Continuous; related construct | Repeated-measures correlation between hospital strength and home functional performance. |
| Range of motion/joint movement | Hospital goniometry/range-of-motion assessment. | Links sensor system elbow and knee goniometry recorded at home on the dominant side. | Continuous; same or related construct | Association and consistency analyses between hospital-based and home-based joint movement measures. |
| Mobility/walking capacity | 10-metre walk test, including spontaneous and fast gait speed and 2-min walk test. | Garmin-derived activity metrics, including step count, distance, activity type, duration and intensity. | Continuous; related construct | Repeated-measures correlation and/or mixed-model association between hospital walking capacity and real-world activity metrics. |
| Cardiorespiratory and sleep context | No direct hospital comparator unless clinically indicated. | Garmin-derived heart rate, respiratory rate, oxygen saturation and sleep quality. | Continuous; contextual/exploratory | Descriptive and exploratory analyses to contextualise activity and functional measures rather than primary home-hospital comparator analysis. |
DT4RD, digital tools for rare disorders; FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; MFM, motor function measure; NSAA, North Star Ambulatory Assessment; NSAD, North Star Assessment for Limb-Girdle-Type Muscular Dystrophies; PEF, peak expiratory flow; PUL, performance of upper limb; TANS, Transition Assessment North Star.
For variables measuring related but non-identical constructs, associations between hospital-based and home-based measures will be examined according to variable type. Repeated-measures correlations will be used for associations between continuous variables. χ2 tests will be used for associations between categorical variables. One-way ANOVA will be used when continuous home-based variables are compared across hospital-based categorical score levels. These analyses will evaluate the consistency and clinical interpretability of home-based digital measures in relation to established hospital-based assessments.
A final report will summarise findings after all subjects have completed the study.
Ethics and dissemination
The study was approved in France by the Comité de Protection des Personnes Sud-Est III on 21 February 2023 (National Number ID-RCB 2022-A02749-34). UK approval was granted by the Health Research Authority and Health and Care Research Wales on 4 March 2024 (IRAS project ID 331474). The protocol has been registered on ClinicalTrials.gov under the number NCT05798325. All participants will be provided with verbal and written information about the study and its procedures before providing written informed consent. Data will be anonymised and handled in accordance with GDPR, French CNIL regulations (MR-001) and applicable national data-protection requirements. To ensure the confidentiality of research participants throughout the study, all data will be collected and stored with restricted access according to current standards for hardware and software security, as required by applicable international, national and European data-protection legislation. Data processing will follow the technical and organisational measures required under Article 32 of the EU General Data Protection Regulation 2016/679. The software platform hosting European patient data records is GDPR-compliant, and all European patient data will be held on a European-hosted server. The Atom5 platform operates in compliance with industry standards for quality management and data security and is FDA 21 CFR Part 11 and GDPR compliant. Results will be communicated through peer-reviewed publications, conference presentations and lay reports.
Discussion and perspectives
Neuromuscular diseases are commonly monitored using standardised clinical assessments performed during hospital visits. These assessments remain essential for recruitment, clinical characterisation, safety oversight and interpretation of disease progression, but they provide only intermittent information and may not fully capture how patients function in their usual environment.6 Remote digital assessments may complement hospital-based evaluations by capturing repeated, home-based measurements of mobility, functional performance, respiratory function, activity, sleep and patient-reported experience. This approach is consistent with the growing use of RWD and decentralised elements in clinical research, provided that digital measures are clinically meaningful, technically robust and interpretable.1–5
The main expected contribution of this study is not to establish clinical efficacy or validate a definitive digital endpoint, but to determine whether the DT4RD framework can reliably support longitudinal home-based data collection. The primary outcome, data recovery rate, will provide evidence on the feasibility of collecting usable data across several modalities, including wearable activity monitoring, electronic goniometry, video-recorded motor tasks, digital questionnaires and optional home spirometry. Secondary analyses will assess usability, technical robustness, repeatability and consistency between home-based and hospital-based measures. These results should help identify which digital measures are sufficiently reliable and acceptable for further validation and which require refinement before use in larger natural history studies or decentralised clinical trials.
The DT4RD framework is intended as a proof-of-concept infrastructure for researchers, clinicians and patient organisations interested in remote assessment of rare neuromuscular disorders. Its potential value lies in the integration of several complementary tools within a single operational model: hospital-based anchoring visits, standardised home-based tasks, passive and active digital data capture, secure data transfer, clinician-facing visualisation and patient-support procedures. Digital measures may convert episodic clinic-based assessment into more continuous observation of function in daily life, particularly when multimodal data are collected through connected technologies.16 17 If feasible, this model could support future studies by reducing the dependence on frequent hospital visits, increasing the amount of longitudinal functional information available between visits and improving the ecological validity of outcome assessment.
Although developed for rare neuromuscular diseases, the framework could also be adapted to other rare and less rare disorders in which mobility, functional performance or activity in daily life are clinically relevant outcomes. This may include conditions affecting gait, upper-limb function, fatigue, balance, respiratory function or participation in daily activities. The framework may therefore be particularly relevant for multicentre studies in rare diseases, where recruitment is limited and repeated in-person assessments can be burdensome for patients and families.18 However, its principles may also be applicable to broader clinical populations after appropriate adaptation and validation. Such transfer would require careful selection of disease-relevant constructs, predefined home–hospital comparator measures and validation against established clinical assessments in each new population.
Dissemination of the DT4RD framework will be led by the clinical, technical and patient-advocacy partners of the consortium. Study findings will be shared through peer-reviewed publications, conference presentations and lay summaries for patient communities. In addition to reporting overall feasibility results, future dissemination should include practical information on implementation, such as participant training procedures, data-flow architecture, data-quality checks, predefined home–hospital comparator measures and lessons learnt from technical failures or missing data. This information will be important if other research groups wish to adapt the framework to different neuromuscular diseases, other rare disease populations or future decentralised clinical trial designs.
Future work will depend on the feasibility and usability results of the present study. If the framework achieves acceptable data recovery and participant engagement, subsequent studies should evaluate the validity, responsiveness and clinical interpretability of selected digital measures in larger and more homogeneous disease cohorts. Wearable-derived endpoints have already shown promise in neuromuscular diseases, including qualification of SV95C in ambulant boys with DMD and emerging activity-based endpoints in DMD.11–13 However, additional work will be needed to determine which DT4RD measures are most meaningful to patients, which are sensitive to change over time and which could support future endpoint development. In this way, DT4RD should be viewed as an initial implementation and evaluation step toward a more generalisable framework for remote, patient-centred assessment of mobility and functional performance.
Supplementary material
Acknowledgements
The DT4RD Consortium would like to express special thanks to Cécile Ollivier for managing the grant application and Christine Fetro for her decisive support.
Footnotes
Funding: The DT4RD programme has received funding from the European Union’s Horizon 2020 research and innovation programme under the EJP RD COFUND-EJP N°825575. Additional support for sponsoring and organising the work was provided by the Association Institute of Myology and all the partners of the DT4RD consortium as agreed in the Grant and Consortium agreements. The main funders had no role in study design; collection, management, analysis and interpretation of data; writing of the report and the decision to submit the report for publication.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2026-121014).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Consent obtained directly from patient(s)
Patient and public involvement: Patients and/or the public were involved in the design, or conduct, or reporting or dissemination plans of this research. Refer to the Methods section for further details.
Data availability statement
No data are available.
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