Smartphone-Based Tele-Rehabilitation for Post-Stroke Motor Recovery

Thesis Abstract

This study addresses the increasing gap in access to effective post-stroke motor rehabilitation by evaluating a smartphone-based tele-rehabilitation (TR) program designed to augment conventional therapy with home-based, technology-driven exercise and monitoring. The problem centers on limited patient access to in-clinic rehabilitation, variable adherence to home exercises, and insufficient long-term motor recovery data in the post-stroke population. The aim is to determine the effectiveness, adherence, and user experience of a structured TR platform that delivers remote-guided motor therapy, real-time feedback, and progress monitoring. Specific objectives include (1) assessing the impact of the TR program on upper-limb motor function using the Fugl-Meyer Assessment for the Upper Extremity (FMA-UE) at 6 and 12 weeks, (2) evaluating changes in functional activity via the Stroke Rehabilitation Assessment of Movement (STREAM) and the Barthel Index, (3) examining adherence rates and factors predicting engagement through mixed-methods measures, (4) exploring user satisfaction and usability using the System Usability Scale (SUS) and qualitative interviews, and (5) identifying moderators such as baseline impairment, age, and technological literacy on rehabilitation outcomes. A concurrent mixed-methods design will be employed. The quantitative strand will recruit 180 adults within three months post-stroke, representing diverse etiologies and severities, from five metropolitan hospitals. Participants will be randomized into a 12-week smartphone TR intervention plus standard care (n=90) versus standard care alone (n=90). The TR program integrates motion-tracking via built-in smartphone sensors and a wearable inertial measurement unit, tele-coaching sessions, exercise libraries based on evidence-based neurorehabilitation protocols, gamified progress feedback, and caregiver-assisted reporting. Data collection instruments include FMA-UE, STREAM, Barthel Index, SUS, adherence logs, and accelerometer-derived activity metrics. The qualitative strand will involve purposive sampling of 30 participants (and 15 caregivers) from the TR group for semi-structured interviews at the end of the intervention to capture perceived barriers, facilitators, and contextual factors influencing engagement. Validity and reliability of instruments will be ensured through established psychometric properties and pilot testing. Data analysis will use intention-to-treat principles. Quantitative analysis will involve repeated-measures ANOVA to detect time-by-group interactions on motor function and activity measures, multiple regression to identify predictors of adherence and outcomes, and mediation analysis to explore whether adherence mediates the effect of TR on motor recovery. For the accelerometer data, mixed-effects models will account for within-subject correlations over time. The qualitative data will be analyzed using thematic analysis guided by Braun and Clarke, with triangulation to integrate quantitative and qualitative findings. The study will be interpreted within the theoretical framework of the Social Cognitive Theory and the Technology Acceptance Model, to understand self-efficacy, outcome expectations, and user adoption as mechanisms driving rehabilitation outcomes. Expected findings include (a) statistically significant improvement in FMA-UE and STREAM scores in the TR group compared with controls at 12 weeks, with moderate to large effect sizes; (b) higher adherence and greater engagement predicting superior motor gains; (c) positive perceptions of usability and satisfaction with the TR platform, moderated by initial technological literacy and age; (d) identification of contextual facilitators such as caregiver support and home environment, and barriers including technical difficulties and connectivity issues. The study contributes to knowledge by providing rigorous, randomized, controlled evidence on the clinical effectiveness of smartphone-based TR for post-stroke motor recovery, delineating adherence as a key mediator, and clarifying how theoretical constructs from Social Cognitive Theory and Technology Acceptance Theory translate into real-world rehabilitation outcomes. It also offers practical guidance on scalable deployment, including integration with standard care pathways, data privacy considerations, and strategies to optimize user engagement among older adults. The main conclusion is that smartphone-based TR can produce meaningful motor recovery and functional gains when embedded within a structured, user-centered framework and supported by caregiver involvement, with adherence and usability being critical determinants of success. Recommendations include optimizing sensor integration for accurate motion capture, enhancing adaptive feedback to sustain motivation, providing training sessions for users with limited digital literacy, and conducting long-term follow-up to assess maintenance of gains and cost-effectiveness analyses.