Development and Evaluation of a Tele-rehabilitation Platform for Post-Stroke Care | Blazingprojects Postgraduate Thesis
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Development and Evaluation of a Tele-rehabilitation Platform for Post-Stroke Care

 

Table Of Contents


Chapter ONE

INTRODUCTION

  • 1.1Introduction to Tele-rehabilitation for Post-Stroke Care
  • 1.2Background of Tele-Rehabilitation in Post-Stroke Recovery
  • 1.3Statement of the Problem in Access and Outcomes Post-Stroke
  • 1.4Aim and Objectives of the Tele-Rehabilitation Platform Study
  • 1.5Research Questions Guiding Platform Development and Evaluation
  • 1.6Research Hypotheses on Efficacy and Usability of Tele-Rehab
  • 1.7Significance of Tele-Rehabilitation Platform for Stakeholders
  • 1.8Scope and Delimitations of the Study Setting and Population
  • 1.9Limitations Encountered in Tele-Rehabilitation Research
  • 1.10Organisation of the Study and Chapter Overview
  • 1.11Operational Definition of Terms in Tele-Rehabilitation for Post-Stroke Care

Chapter TWO

LITERATURE REVIEW

  • 2.1Conceptual Review: Tele-Rehabilitation Concepts for Stroke Recovery
  • 2.2Conceptual Review: Technology-Enabled Rehabilitation Interventions
  • 2.3Conceptual Review: User-Centered Design in rehabilitative Telehealth
  • 2.4Conceptual Review: Outcomes and Measures in Stroke Rehabilitation
  • 2.5Theoretical Framework: Technology Acceptance Model (TAM) in Tele-Rehab
  • 2.6Theoretical Framework: Unified Theory of Acceptance and Use of Technology (UTAUT) in Healthcare
  • 2.7Theoretical Framework: Self-Efficacy Theory in Patient Adherence to Tele-Rehab
  • 2.8Empirical Review: Randomized Trials of Tele-Rehabilitation for Stroke
  • 2.9Empirical Review: Usability and Acceptability Studies in Tele-Rehab
  • 2.10Empirical Review: Cost-Effectiveness of Tele-Rehabilitation for Stroke
  • 2.11Identified Gaps in the Literature on Tele-Rehabilitation Post-Stroke
  • 2.12Conceptual Model: Integrated Tele-Rehabilitation Framework for Post-Stroke Care

Chapter THREE

RESEARCH METHODOLOGY

  • 3.1Research Design: Design-Implementation-Evaluation of a Tele-Rehabilitation Platform
  • 3.2Philosophical Paradigm: Pragmatism for Mixed-Methods Evaluation
  • 3.3Population of the Study: Post-Stroke Patients, Caregivers and Clinicians
  • 3.4Sample Size and Sampling Technique for Each Cohort
  • 3.5Sources and Instruments of Data Collection: System Metrics and Survey Tools
  • 3.6Validity and Reliability of Instruments: Psychometrics for Scales and App Analytics
  • 3.7Intervention Design: Platform Features, Protocols, and Care Pathways
  • 3.8Data Analysis Methods: Quantitative, Qualitative, and Mixed-Methods
  • 3.9Model Specification: Output Metrics for Rehabilitation Progress and Engagement
  • 3.10Ethical Considerations: Informed Consent, Privacy, and Data Security

Chapter FOUR

DATA PRESENTATION AND ANALYSIS

  • ANALYSIS AND DISCUSSION OF FINDINGS
  • 4.1Data Presentation: Participant Demographics and Baseline Characteristics
  • 4.2Descriptive Analysis: Platform Usage, Adherence, and Intervention Reach
  • 4.3Descriptive Analysis: Functional and Activity-Based Outcomes
  • 4.4Hypotheses Testing: Efficacy of Tele-Rehabilitation on Motor Recovery
  • 4.5Hypotheses Testing: Impact on Activities of Daily Living and Quality of Life
  • 4.6Hypotheses Testing: User Satisfaction and Usability of the Platform
  • 4.7Interpretation of Results: Clinical Significance and Practical Implications
  • 4.8Discussion in Relation to Existing Literature: Convergences and Contrasts

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • CONCLUSION AND RECOMMENDATIONS
  • 5.1Summary of Key Findings Across Design, Implementation, and Evaluation
  • 5.2Conclusions Regarding Efficacy, Usability, and Implementation Feasibility
  • 5.3Contribution to Knowledge: Advancing Tele-Rehabilitation for Stroke
  • 5.4Recommendations for Stakeholders: Clinicians, Developers, and Policymakers
  • 5.5Suggestions for Further Studies: Long-Term Outcomes and Diverse Settings

Thesis Abstract

Stroke survivors often face limited access to intensive rehabilitation services due to geographic, transportation, and resource constraints, leading to suboptimal functional recovery and reintegration into daily life. This study addresses the persistent gap by developing and evaluating a tele-rehabilitation platform that delivers multimodal post-stroke rehabilitation within home and community settings, integrating motor, cognitive, and speech therapies with remote clinician supervision. The aim is to design, implement, and rigorously evaluate a scalable tele-rehabilitation solution that enhances adherence, accelerates motor recovery, and improves health-related quality of life for stroke survivors and their caregivers. The specific objectives are (1) to identify user requirements and barriers to home-based rehabilitation through a mixed-methods needs assessment; (2) to develop a modular tele-rehabilitation platform incorporating sensor-based movement monitoring, guideline-driven exercise programs, remote coaching, and outcome tracking aligned with standard post-stroke care pathways; (3) to evaluate the platform’s usability, feasibility, and acceptability with 120 stroke survivors and 60 caregivers over a 12-week pilot; (4) to determine preliminary effectiveness on motor function (Fugl-Meyer Assessment-Upper Extremity), activities of daily living (Barthel Index), and quality of life (Stroke-Specific Quality of Life Scale) using a quasi-experimental design; (5) to examine implementation processes, fidelity, and contextual factors via the Consolidated Framework for Implementation Research (CFIR); and (6) to model cost-effectiveness relative to usual care. A mixed-methods research design will be employed, beginning with a qualitative needs assessment using thematic analysis of semi-structured interviews with 40 stroke survivors, 20 caregivers, and 15 clinicians to inform platform design. The subsequent feasibility and pilot phases will enroll 120 stroke survivors via outpatient and community-based clinics and 60 informal caregivers, with stratified sampling to ensure representation by age, sex, severity, and urban-rural residence. Data collection instruments will include validated motor and functional outcome measures (Fugl-Meyer Assessment - Upper Extremity, Action Research Arm Test, Modified Rankin Scale), activities of daily living (Barthel Index), mobility (Timed Up and Go), and quality-of-life outcomes (Stroke-Specific Quality of Life Scale). Usability will be assessed with the System Usability Scale and the User Engagement Scale; adherence will be tracked via platform analytics (logins, exercise completion, coaching interactions). For the economic evaluation, direct medical and non-medical costs will be collected to perform a cost-utility analysis from a health-system perspective, expressing outcomes as Quality-Adjusted Life Years (QALYs) obtained from the EQ-5D-5L. Quantitative analyses will include repeated-measures ANOVA and linear mixed-effects models to compare pre- and post-intervention outcomes, adjusting for covariates such as baseline impairment and comorbidities. Regression analyses will identify predictors of adherence and functional gains. The qualitative data will be analyzed thematically, with triangulation to inform refinements in platform design and implementation strategies. A convergent mixed-methods approach will integrate quantitative outcomes with qualitative insights to explain differential responses and contextualize findings. The theoretical framework combines the Biopsychosocial Model of Stroke Rehabilitation with the Technology Acceptance Model (TAM2) and the CFIR to guide design, deployment, and evaluation. Expected findings include improved upper-extremity motor function (mean Fugl-Meyer increase >8 points), enhanced independence in daily activities (Barthel index improvement >10 points), and reported gains in perceived quality of life, alongside high usability scores (SUS > 70) and acceptable adherence rates (?75% of prescribed sessions completed). The study is anticipated to demonstrate favorable short-term cost-effectiveness relative to standard care, driven by reduced travel burdens and optimized therapy dosing. The contribution to knowledge lies in empirically valid evidence for a scalable, patient-centered tele-rehabilitation model that integrates motor, cognitive, and communication therapy with remote clinical oversight, advancing implementation science in post-stroke care. The main conclusion is that a well-designed tele-rehabilitation platform can augment conventional rehabilitation by enabling timely, tailored, and accessible therapy, with positive implications for outcomes and health-system efficiency. Recommendations include refining interoperability standards, expanding caregiver engagement modules, conducting a larger randomized controlled trial to confirm efficacy, and exploring integration with community-based rehabilitation networks to sustain long-term adoption.

Thesis Overview

Tele-rehabilitation for post-stroke care aims to extend and optimize rehabilitation services by delivering therapy through digital platforms that patients can access remotely. This research explores whether a dedicated tele-rehabilitation platform can improve functional recovery, increase accessibility, and sustain adherence to therapy after stroke. Why it matters: Stroke often leaves people with mobility impairments and limited access to in-person rehab due to transportation barriers, cost, or clinician shortages. Traditional rehabilitation can be inconsistent in frequency and intensity. Tele-rehabilitation has the potential to deliver tailored exercises, real-time feedback, remote monitoring, and psychosocial support, addressing gaps in continuity of care and potentially reducing long-term disability and caregiver burden. What problem or knowledge gap it addresses: While small-scale studies suggest benefits of tele-rehabilitation, there is a need for robust design, implementation, and evaluation of a comprehensive platform that integrates motor and cognitive therapies, mood monitoring, and remote clinician oversight in a real-world setting. This study conceptualizes, builds, and evaluates a platform tailored to post-stroke needs and investigates its impact on functional outcomes, adherence, user satisfaction, and cost-effectiveness. What the researcher will do step by step: - Phase 1: needs assessment and design - Conduct a mixed-methods needs assessment with stroke survivors, caregivers, and physiotherapists to identify requirements. - Define platform architecture, user roles, safety features, and evidence-based exercise modules grounded in motor recovery principles. - Phase 2: implementation - Develop a multimodal tele-rehabilitation platform incorporating video-guided exercises, progress tracking, automated reminders, and clinician dashboards. - Pilot the platform with 20–30 stroke survivors to refine usability and safety. - Phase 3: evaluation - Conduct a randomized controlled trial with 120 participants, allocated to tele-rehabilitation plus standard care vs. standard care alone for 12 weeks. - Data collection includes functional measures (e.g., Fugl-Meyer Assessment, Barthel Index), adherence metrics (login frequency, completion rate), quality of life (Stroke Impact Scale), and user satisfaction surveys. - Data analysis uses intention-to-treat principles; quantitative data analyzed with regression analyses and repeated-measures ANOVA to assess changes over time; qualitative feedback from interviews analyzed using thematic analysis. - Phase 4: economic and implementation assessment - Perform a cost-effectiveness analysis from the health system perspective and assess facilitators and barriers to adoption through stakeholder interviews. Expected contribution and outcome: The study will provide rigorous evidence on the effectiveness, usability, and economic viability of a integrated tele-rehabilitation platform for post-stroke care, offering a scalable approach to improving recovery trajectories and access to therapy. Potential implications: If successful, the platform could inform clinical guidelines, support policy decisions on digital rehabilitation, and guide future iterations to optimize long-term adherence and outcomes.

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