Ortega-Auriol Pablo, Besier Thor, McMorland Angus J C
Auckland Bioengineering Institute & Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland, New Zealand.
Auckland Bioengineering Institute & Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland, New Zealand.
J Electromyogr Kinesiol. 2025 Feb;80:102968. doi: 10.1016/j.jelekin.2024.102968. Epub 2024 Dec 21.
This study investigates the effect of different normalisation methods on muscle synergy extraction from EMG data collected while walking in typically developing young people. Six methods were evaluated: Raw, Within-Trial Maximum, Inter-Trial Maximum, Task-Specific Maximum, Magnitude Percentile, and Unit Variance. Eighteen healthy children aged 8-15 participated, performing walking trials while their EMG signals were recorded and processed. Synergies were extracted using non-negative matrix factorisation, and the influence of normalisation methods on synergy complexity, structure, and activation coefficients was assessed. Normalisation choice significantly influenced synergy number, structure, and temporal characteristics. TSM and ITM methods yielded more consistent synergies, while MP and WTM exhibited greater variability. This study highlights the importance of selecting appropriate normalisation methods for robust muscle synergy analyses, enhancing understanding of motor control strategies, and contributing to a unified processing workflow.
本研究调查了不同归一化方法对从典型发育的年轻人行走时收集的肌电图(EMG)数据中提取肌肉协同作用的影响。评估了六种方法:原始数据、试验内最大值、试验间最大值、任务特定最大值、幅度百分位数和单位方差。18名8 - 15岁的健康儿童参与其中,在进行行走试验时记录并处理他们的EMG信号。使用非负矩阵分解提取协同作用,并评估归一化方法对协同作用复杂性、结构和激活系数的影响。归一化方法的选择显著影响协同作用的数量、结构和时间特征。任务特定最大值(TSM)和试验间最大值(ITM)方法产生的协同作用更一致,而幅度百分位数(MP)和试验内最大值(WTM)表现出更大的变异性。本研究强调了选择合适的归一化方法对于稳健的肌肉协同作用分析、增强对运动控制策略的理解以及促进统一处理工作流程的重要性。