提出两种新指标,精准量化运动中关节协调策略的时空变化。
JcvPCA and JsvCRP : a set of metrics to evaluate changes in joint coordination strategies
- 用主成分分析衡量各关节贡献的变化趋势。
- 用连续相对相位评估关节间同步性的差异。
- 适合康复、人因工程等需分析运动协调的研究者使用。
描述关节间协调变化面临重大挑战,需同时分析多自由度运动关系及其时间演化。现有指标难以提供生理上合理的结果,无法兼顾时空特性。本文提出两种新指标:基于主成分分析的关节贡献变异(JcvPCA),用于评估一系列运动中各关节贡献的变化;基于连续相对相位的关节同步性变异(JsvCRP),用于测量两组运动数据间关节间时间同步性的差异。我们先阐述每个指标的推导过程,再通过模拟与实验数据验证其有效性,这些数据来自相同运动任务但采用不同协调策略的情况。结果表明,该方法能有效区分不同协调策略,为运动中关节协作提供有意义的洞察。该方法在人因工程和临床康复领域具有重要应用潜力,可用于评估上肢外骨骼在工业环境中的影响,或监测神经系统康复患者的进展。
原文摘要 · Abstract (English)
Characterizing changes in inter-joint coordination presents significant challenges, as it necessitates the examination of relationships between multiple degrees of freedom during movements and their temporal evolution. Existing metrics are inadequate in providing physiologically coherent results that document both the temporal and spatial aspects of inter-joint coordination. In this article, we introduce two novel metrics to enhance the analysis of inter-joint coordination. The first metric, Joint Contribution Variation based on Principal Component Analysis (JcvPCA), evaluates the variation in each joint's contribution during series of movements. The second metric, Joint Synchronization Variation based on Continuous Relative Phase (JsvCRP), measures the variation in temporal synchronization among joints between two movement datasets. We begin by presenting each metric and explaining their derivation. We then demonstrate the application of these metrics using simulated and experimental datasets involving identical movement tasks performed with distinct coordination strategies. The results show that these metrics can successfully differentiate between unique coordination strategies, providing meaningful insights into joint collaboration during movement. These metrics hold significant potential for fields such as ergonomics and clinical rehabilitation, where a precise understanding of the evolution of inter-joint coordination strategies is crucial. Potential applications include evaluating the effects of upper limb exoskeletons in industrial settings or monitoring the progress of patients undergoing neurological rehabilitation.
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