Immersive Extended Reality for Lower Limb Rehabilitation: Design, Deployment, and Pilot Study

This thesis presents the design, deployment, and pilot study of an immersive extended-reality (XR) rehabilitation system integrated with a ceiling-mounted dynamic body-weight support device (Vector Gait and Safety System), aimed at improving lower-limb rehabilitation out- comes. The implemented system combined immersive virtual tasks—such as Touch Wall, Ball Launcher, Obstacle Dodge, and Stepping Stones—with real-time movement tracking, enabling detailed kinematic analysis and personalized therapy. A pilot study conducted at Sunnyview Rehabilitation Hospital involved seven patients with various mobility impairments, providing quantitative performance metrics and quali- tative user feedback. Results demonstrated consistent patient engagement, measurable im- provements in gait speed and task efficiency over repeated sessions, as well as emerging adaptive movement strategies. Patients reported high motivation, comfort, and satisfaction with the XR-based tasks, supported by positive therapist observations highlighting enhanced patient autonomy and reduced self-consciousness during rehabilitation. The thesis concludes by discussing how this work fits within the broader landscape of extended reality (XR) and artificial intelligence (AI) in rehabilitation. The discussion section specifically examines how the findings relate to general trends in XR and AI-based rehabil- itation, highlighting both the opportunities these technologies present and the challenges they pose. Future work will focus on integrating real-time AI-driven adaptation, natural language interfaces, and expanded rehabilitation task libraries, with particular emphasis on accommodating diverse neurological populations, including those recovering from traumatic brain injury (TBI). Overall, this research contributes significantly to the advancement of intelligent, adaptive, and patient-centered XR rehabilitation solutions, offering substantial promise for transforming clinical practice and enhancing patient recovery outcomes.

Publication Details

Journal
Scholars Archive - University at Albany (University at Albany, State University of New York)
Published
2025-01-01
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
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article

Immersive Extended Reality for Lower Limb Rehabilitation: Design, Deployment, and Pilot Study

Scholars Archive - University at Albany (University at Albany, State University of New York)
Stroke Rehabilitation and Recovery
article

Immersive Extended Reality for Lower Limb Rehabilitation: Design, Deployment, and Pilot Study

article en

Abstract

This thesis presents the design, deployment, and pilot study of an immersive extended-reality (XR) rehabilitation system integrated with a ceiling-mounted dynamic body-weight support device (Vector Gait and Safety System), aimed at improving lower-limb rehabilitation out- comes. The implemented system combined immersive virtual tasks—such as Touch Wall, Ball Launcher, Obstacle Dodge, and Stepping Stones—with real-time movement tracking, enabling detailed kinematic analysis and personalized therapy. A pilot study conducted at Sunnyview Rehabilitation Hospital involved seven patients with various mobility impairments, providing quantitative performance metrics and quali- tative user feedback. Results demonstrated consistent patient engagement, measurable im- provements in gait speed and task efficiency over repeated sessions, as well as emerging adaptive movement strategies. Patients reported high motivation, comfort, and satisfaction with the XR-based tasks, supported by positive therapist observations highlighting enhanced patient autonomy and reduced self-consciousness during rehabilitation. The thesis concludes by discussing how this work fits within the broader landscape of extended reality (XR) and artificial intelligence (AI) in rehabilitation. The discussion section specifically examines how the findings relate to general trends in XR and AI-based rehabil- itation, highlighting both the opportunities these technologies present and the challenges they pose. Future work will focus on integrating real-time AI-driven adaptation, natural language interfaces, and expanded rehabilitation task libraries, with particular emphasis on accommodating diverse neurological populations, including those recovering from traumatic brain injury (TBI). Overall, this research contributes significantly to the advancement of intelligent, adaptive, and patient-centered XR rehabilitation solutions, offering substantial promise for transforming clinical practice and enhancing patient recovery outcomes.

Scholars Archive - University at Albany (University at Albany, State University of New York)
Quality Education
Openalex Percentile: Top 44%
Stroke Rehabilitation and Recovery
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Immersive Extended Reality for Lower Limb Rehabilitation: Design, Deployment, and Pilot Study · Scholars Archive - University at Albany (University at Albany, State University of New York) (2025) | TGRS Research Map | TGRS