UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language
Chongyang Wang, Yuan Feng, Lingxiao Zhong, Siyi Zhu, Chi Zhang, Siqi, Zheng, Chen Liang, Yuntao Wang, Chengqi He, Chun Yu, and Yuanchun Shi

TL;DR
UbiPhysio is a framework that provides natural language descriptions and feedback on physical actions to support daily activities, fitness, and rehabilitation, leveraging biomechanical data and domain knowledge.
Contribution
It introduces a novel system combining biomechanical action data with expert-like feedback in natural language for health and fitness applications.
Findings
Effective action description from biomechanical features.
Positive user feedback from physiotherapists and users.
Potential for deployment in real-life settings without specialized devices.
Abstract
We introduce UbiPhysio, a milestone framework that delivers fine-grained action description and feedback in natural language to support people's daily functioning, fitness, and rehabilitation activities. This expert-like capability assists users in properly executing actions and maintaining engagement in remote fitness and rehabilitation programs. Specifically, the proposed UbiPhysio framework comprises a fine-grained action descriptor and a knowledge retrieval-enhanced feedback module. The action descriptor translates action data, represented by a set of biomechanical movement features we designed based on clinical priors, into textual descriptions of action types and potential movement patterns. Building on physiotherapeutic domain knowledge, the feedback module provides clear and engaging expert feedback. We evaluated UbiPhysio's performance through extensive experiments with data…
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Taxonomy
TopicsHuman Pose and Action Recognition · Context-Aware Activity Recognition Systems
