Purpose: Regular exercise can reduce the symptoms of Parkinson’s disease, a common neurodegenerative disorder. The Rock Steady Boxing organization created an exercise program for people with Parkinson’s Disease (pwPD) modelled after traditional boxing. The purpose of this study was to better understand the physical function, exercise beliefs, contextual factors, class experiences and outcome perceptions of pwPD participating in Rock Steady Boxing. Materials and methods: A pragmatic qualitative approach of semi-structured interviews and class observations was supplemented by cross-sectional physical function measures. Results: Ten study participants were community dwelling adults with Parkinson’s Disease, participating in Rock Steady Boxing two to three times a week for an average of 10.6 (6.2) months. Most participants (7/10) had good mobility with Timed Up and Go scores below the 14.8 second average for community dwelling pwPD (7/10) and Parkinson’s Disease Questionnaire-39 Mobility Scores < 50% (8/10). Participants (9/10) had good exercise self-efficacy, with average scores on the Short Self-efficacy for Exercise Scale > 3/5. Thematic analysis revealed a history of exercise and strong exercise beliefs positively influenced participation. Rock Steady Boxing provided valued social interactions and offered individualized attention through personalized modifications. Conclusions: Instructor enthusiasm, program modifiability and social support drive participation and provide a challenge for differing abilities. RSB is a valued community offering for pwPD.

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

Early mobilization (EM) can mitigate hospital-acquired deconditioning by preserving prehospital functional status. EM measurement is challenging due to concerns such as accuracy and patient comfort. Palarum PUP^® Smart Socks were designed for the hospital setting to track step count and time out of bed. The purpose of this study was to evaluate the inter-method reliability of the Palarum PUP^® Smart Socks compared with the Opal v1 Mobility Lab system. Using a cross-sectional design, participants wore Smart Socks and six mobility sensors while completing three trials of a 20 m walk at a self-selected pace. Step count, stride length, gait speed, and duration were recorded. Differences between the two measurement systems were assessed using paired t-tests, agreement was evaluated using Bland–Altman analyses, and reliability was assessed using intraclass correlation coefficients (ICCs) with 95% confidence intervals. Fifty-three participants were enrolled (mean age 37.9 ± 16.7 years; 64% female; 75% White; BMI 28.2 ± 5.9 kg/m²). ICCs demonstrated excellent reliability for step count and duration (ICC > 0.90) moderate reliability for gait speed (ICC = 0.52), and poor reliability for stride length (ICC = 0.30). Reliability was statistically significant for step count, gait speed, duration, and stride length (all p < 0.01). Findings support the reliability of Palarum PUP^® Smart Socks among ambulatory adults. By overcoming many limitations of traditional wearables in hospital settings, Smart Socks may be particularly well suited for EM programs. However, further validation is needed among hospitalized adults who may have slower gait speed and/or altered gait patterns.