Rachael Brink Akay

Background: Connected sensor technologies can capture raw data and analyze them using advanced statistical methods such as machine learning or artificial intelligence to generate interpretable behavioral or physiological outcomes. Previous research conducted on connected sensor technologies has focused on design, development, and validation. Published review studies have either summarized general technological solutions to address specific behaviors such as physical activity or focused on remote monitoring solutions in specific patient populations. Objective: This study aimed to map research that focused on using connected sensor technologies to augment rehabilitation services by informing care decisions. Methods: The Population, Concept, and Context framework will be used to define inclusion criteria. Relevant articles published between 2008 to the present will be included if (1) the study enrolled adults (population), (2) the intervention used at least one connected sensor technology and involved data transfer to a clinician so that the data could be used to inform the intervention (concept), and (3) the intervention was within the scope of rehabilitation (context). An initial search strategy will be built in Embase; peer reviewed; and then translated to Ovid MEDLINE ALL, Web of Science Core Collection, and CINAHL. Duplicates will be removed prior to screening articles for inclusion. Two independent reviewers will screen articles in 2 stages: title/abstract and full text. Discrepancies will be resolved through group discussion. Data from eligible articles relevant to population, concept, and context will be extracted. Descriptive statistics will be used to report findings, and relevant outcomes will include the type and frequency of connected sensor used and method of data sharing. Additional details will be narratively summarized and displayed in tables and figures. Key partners will review results to enhance interpretation and trustworthiness. Results: We conducted initial searches to refine the search strategy in February 2024. The results of this scoping review are expected in October 2024. Conclusions: Results from the scoping review will identify critical areas of inquiry to advance the field of technology-augmented rehabilitation. Results will also support the development of a longitudinal model to support long-term health outcomes. Trial Registration: Open Science Framework jys53; https://osf.io/jys53 International Registered Report Identifier (IRRID): DERR1-10.2196/60496

BACKGROUND Connected sensor technologies can capture raw data and analyze them using advanced statistical methods such as machine learning or artificial intelligence to generate interpretable behavioral or physiological outcomes. Previous research conducted on connected sensor technologies has focused on design, development, and validation. Published review studies have either summarized general technological solutions to address specific behaviors such as physical activity or focused on remote monitoring solutions in specific patient populations. OBJECTIVE This study aimed to map research that focused on using connected sensor technologies to augment rehabilitation services by informing care decisions. METHODS The Population, Concept, and Context framework will be used to define inclusion criteria. Relevant articles published between 2008 to the present will be included if (1) the study enrolled adults (population), (2) the intervention used at least one connected sensor technology and involved data transfer to a clinician so that the data could be used to inform the intervention (concept), and (3) the intervention was within the scope of rehabilitation (context). An initial search strategy will be built in Embase; peer reviewed; and then translated to Ovid MEDLINE ALL, Web of Science Core Collection, and CINAHL. Duplicates will be removed prior to screening articles for inclusion. Two independent reviewers will screen articles in 2 stages: title/abstract and full text. Discrepancies will be resolved through group discussion. Data from eligible articles relevant to population, concept, and context will be extracted. Descriptive statistics will be used to report findings, and relevant outcomes will include the type and frequency of connected sensor used and method of data sharing. Additional details will be narratively summarized and displayed in tables and figures. Key partners will review results to enhance interpretation and trustworthiness. RESULTS We conducted initial searches to refine the search strategy in February 2024. The results of this scoping review are expected in October 2024. CONCLUSIONS Results from the scoping review will identify critical areas of inquiry to advance the field of technology-augmented rehabilitation. Results will also support the development of a longitudinal model to support long-term health outcomes. CLINICALTRIAL Open Science Framework jys53; https://osf.io/jys53 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/60496

Objective: This randomized controlled superiority trial will determine if an 18-month telehealth walking exercise self-management program produces clinically meaningful changes in walking exercise sustainability compared to attention-control education for veterans living with lower-limb amputation. Methods: Seventy-eight participants with lower-limb amputation (traumatic or nontraumatic) aged 50 to 89 years will be enrolled. Two groups will complete 6 one-on-one intervention sessions, and 6 group sessions over an 18-month intervention period. The experimental arm will receive a self-management program focusing on increasing walking exercise and the control group will receive attention-control education specific to healthy aging. Daily walking step count (primary outcome) will be continuously monitored using an accelerometer over the 18-month study period. Secondary outcomes are designed to assess potential translation of the walking exercise intervention into conventional amputation care across the Veteran Affairs Amputation System of Care. These secondary outcomes include measures of intervention reach, efficacy, likelihood of clinical adoption, potential for clinical implementation, and ability of participants to maintain long-term exercise behavior. Impact: The unique rehabilitation paradigm used in this study addresses the problem of chronic sedentary lifestyles following lower-limb amputation through a telehealth home-based walking exercise self-management model. The approach includes 18 months of exercise support from clinicians and peers. Trial results will provide rehabilitation knowledge necessary for implementing clinical translation of self-management interventions to sustain walking exercise for veterans living with lower-limb amputation, resulting in a healthier lifestyle.