AI Assisted Quantitative Physiotherapy Technology for Rehabilitation of Older Adults

2026 | Undergraduate Summer Research Fellowship

Awarded to: Patryk Kopacz

Supervisor: Qiyin Fang, Faculty of Engineering

Summary

Post-hospitalization rehabilitation is an important phase of care for older adults. Effective and safe physiotherapy exercise has long been recognized as a key factor for post-hospitalization recovery and improving quality of life. At home exercise is highly challenging in older adults (OldA), and this increases with age. Currently, most technologies applied to older adults focus on self-management, not training. Advancements in real-time measurement of motion patterns and feedback/coaching during training will improve management of at-home rehabilitation in older adults. We propose to develop an AI-assisted at-home physiotherapy rehabilitation technology that provides real-time measurements and guidance during exercise.

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