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PhaseAware:通过边界监测实现可解释的人在回路康复评分

PhaseAware: Interpretable Human-in-the-Loop Rehabilitation Scoring with Boundary Monitoring

Yankai Zheng, Yuhe Liu, Yuxin Ma, Tianci Xue, Jiayuan Tian, Yu Fu, Yuxuan Hu, Jianing Wang, Zichun Xiao, Junya Mu, Shaohui Ma

arXiv 2607.20237首次发表:更新:

AI 中文总结

研究提出PhaseAware框架用于康复质量评估,结合时间骨干与描述符,经骨干条件门控残差路径实现。在深蹲协议测试中表现出色,能生成审查线索,稳定特征表示,为康复评分提供实用可解释方法,利于自动化评估与临床监督结合。

AI 中文摘要

康复评分系统在临床工作流程中能被审查和解释时最为有用。本研究提出了PhaseAware,一个用于持续康复质量评估的紧凑框架,它通过骨干条件门控残差路径将时间骨干与阶段和身体组描述符相结合。该模型在UI - PRMD深蹲协议上进行了评估,并在KIMORE深蹲子集中进一步测试。在UI - PRMD上,PhaseAware的RMSE为0.0230,相对于公认基线降低了88.9%。在KIMORE上也保持了良好性能。除了分数预测,PhaseAware还基于阶段和身体水平敏感性生成结构化审查线索,突出与每个预测最相关的运动阶段和身体区域。其架构采用骨干条件门控残差机制稳定特征表示,适用于资源受限环境。这些线索旨在支持临床医生审查、边界情况监测和人在回路分类,而非自主决策。总体而言,PhaseAware为康复评分提供了一种实用且可解释的方法,有助于将自动化评估整合到信息系统中,同时保留临床医生的监督。

英文摘要

Rehabilitation scoring systems are most useful when their outputs can be reviewed and interpreted within clinical workflows. This study presents PhaseAware, a compact framework for continuous rehabilitation quality assessment that combines a temporal backbone with phase- and body-group descriptors through a backbone-conditioned gated residual pathway. The model was evaluated on the UI-PRMD deep-squat protocol and further tested on the KIMORE squatting subset. On UI-PRMD, PhaseAware achieved an RMSE of 0.0230, corresponding to an 88.9% reduction relative to the accepted baseline. It also maintained favorable performance on KIMORE, suggesting that the phase-aware design transfers across related squatting protocols. In addition to score prediction, PhaseAware generates structured review cues based on phase- and body-level sensitivity, highlighting the movement stages and body regions most relevant to each prediction. The architecture employs a backbone-conditioned gated residual mechanism to stabilize feature representation, supporting use in resource-constrained settings. These cues are intended to support clinician review, boundary-case monitoring, and human-in-the-loop triage rather than autonomous decision-making. Overall, PhaseAware offers a practical and interpretable approach to rehabilitation scoring that may help integrate automated assessment into information systems while preserving clinician oversight.

Comments22 pages, 4 main figures, 3 tables, and 17 supplementary figures. Supplementary Information is included in the same PDF

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