构建临床康复动作数据集，助力智能康复教学系统发展
Low-Back Pain Physical Rehabilitation by Movement Analysis in Clinical Trial
- 构建真实临床环境下的腰痛康复动作数据集
- 支持动作评估、错误识别、空间与时间定位四项挑战
- 适合康复医疗AI研究者与智能康复系统开发者
为推动智能康复教学系统的发展与评估，本文提出一个在临床环境中收集的腰痛康复训练患者动作数据集，并对当前先进的人体运动分析算法进行基准测试。该数据集具有重要价值，因其包含真实康复程序中患者的康复动作。本文介绍的Keraal数据集旨在支持康复智能教学系统（ITS）的研究。它解决了四个关键挑战：动作评估、错误识别、空间定位与时间定位。
原文摘要 · Abstract (English)
To allow the development and assessment of physical rehabilitation by an intelligent tutoring system, we propose a medical dataset of clinical patients carrying out low back-pain rehabilitation exercises and benchmark on state of the art human movement analysis algorithms. This dataset is valuable because it includes rehabilitation motions in a clinical setting with patients in their rehabilitation program. This paper introduces the Keraal dataset, a clinically collected dataset to enable intelligent tutoring systems (ITS) for rehabilitation. It addresses four challenges in exercise monitoring: motion assessment, error recognition, spatial localization, temporal localization
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