Zhao Xin, Zhang Ying, Zhang Yi, Jiang Shuo, Zhang Peng, Yu Jinxu, Yuan Shuai
School of Arts and Design, Yanshan University, Haigang District, Qinhuangdao 066000, China.
Arts Department of Qinhuangdao Vocational and Technical College, Beidaihe District, Qinhuangdao 066100, China.
Biomimetics (Basel). 2025 Jun 29;10(7):419. doi: 10.3390/biomimetics10070419.
Piano-based occupational therapy has emerged as an engaging and effective rehabilitation strategy for improving upper limb motor functions. However, a lack of comprehensive biomechanical modeling, objective rehabilitation assessment, and real-time fatigue monitoring has limited its clinical optimization. This study developed a comprehensive "key-finger-exoskeleton" biomechanical model based on Hill-type muscle dynamics and rigid-body kinematics. A three-dimensional muscle synergy analysis method using non-negative tensor factorization (NTF) was proposed to quantitatively assess rehabilitation effectiveness. Furthermore, a real-time Comprehensive Muscle Fatigue Index (CMFI) based on multi-muscle coordination was designed for fatigue monitoring during therapy. Experimental validations demonstrated that the biomechanical model accurately predicted interaction forces during piano-playing tasks. After three weeks of therapy, patients exhibited increased synergy modes and significantly improved similarities with healthy subjects across spatial, temporal, and frequency domains, particularly in the temporal domain. The CMFI showed strong correlation (r > 0.83, < 0.001) with subjective fatigue ratings, confirming its effectiveness in real-time fatigue assessment and training adjustment. The integration of biomechanical modeling, synergy-based rehabilitation evaluation, and real-time fatigue monitoring offers an objective, quantitative framework for optimizing piano-based rehabilitation. These findings provide important foundations for developing intelligent, adaptive rehabilitation systems.
基于钢琴的职业治疗已成为一种引人入胜且有效的康复策略,用于改善上肢运动功能。然而,缺乏全面的生物力学建模、客观的康复评估和实时疲劳监测限制了其临床优化。本研究基于希尔型肌肉动力学和刚体运动学,开发了一种全面的“关键手指外骨骼”生物力学模型。提出了一种使用非负张量分解(NTF)的三维肌肉协同分析方法,以定量评估康复效果。此外,设计了一种基于多肌肉协调的实时综合肌肉疲劳指数(CMFI),用于治疗期间的疲劳监测。实验验证表明,该生物力学模型能够准确预测钢琴演奏任务中的相互作用力。经过三周的治疗,患者在空间、时间和频率域中表现出增加的协同模式,并且与健康受试者的相似性显著提高,特别是在时间域中。CMFI与主观疲劳评分显示出强相关性(r > 0.83,< 0.001),证实了其在实时疲劳评估和训练调整中的有效性。生物力学建模、基于协同的康复评估和实时疲劳监测的整合为优化基于钢琴的康复提供了一个客观、定量的框架。这些发现为开发智能、自适应康复系统提供了重要基础。