摘要
目的采用样本熵(SampEn)评价表面肌电信号(sEMG)的复杂性,进而探索sEMG复杂性-肌力关系。方法 10名受试者双侧手臂分别执行一系列不同肌力水平的屈肘运动,同时采集肱二头肌sEMG信号和屈肘力矩。采用Samp En分析sEMG复杂性并计算sEMG幅度均方根(RMS),然后通过线性回归与非线性(指数)回归分析分别建立sEMG复杂性以及幅度与肌力之间的关系。结果对不同受试者,sEMG幅度-肌力同时呈现线性和非线性关系,相比之下,sEMG复杂性-肌力呈现一致的线性关系且线性度更好(决定系数)。结论健康受试者屈肘肌力与sEMG复杂性的关系,可以作为评价神经肌肉系统状态与功能的新方法。
Objective To investigate the relationship between surface EMG and muscle strength using sample entropy（ Samp En） analysis of the s EMG signal to quantify its complexity. Methods Ten healthy subjects performed a series of isometric elbow flexion tasks with varying muscle strength on each side. Both the s EMG signal from biceps brachii muscle and the elbow flexion torque signal were recorded. The root-mean-square（ RMS） amplitude and Samp En of s EMG were calculated for establishing the s EMG-torque relationship by using both linear and nonlinear（ exponential） regression analysis,respectively. Results The s EMG amplitudetorque relationship appeared to be linear and nonlinear across different subjects,while the s EMG complexitytorque relationship was found to be quite linear across all subjects（ coefficient determination R^2 〉0. 938）.Conclusion The relationship between the complexity of s EMG and muscle torque was found to have more linearity than the conventional s EMG amplitude-torque relationship in healthy controls. This finding offers a novel investigative approach to assess the state and function of the neuromuscular system.
出处
《航天医学与医学工程》
CAS
CSCD
北大核心
2016年第2期120-126,共7页
Space Medicine & Medical Engineering
基金
国家自然科学基金(61271138
61401421)
中央高校基本科研业务费专项资金(WK2100230014)
关键词
表面肌电信号
肌力
复杂性分析
样本熵
均方根幅值
surface electromyogram
muscle strength
complexity analysis
sample entropy
root mean square
作者简介
通讯作者：张旭xuzhang90@ustc．edu．cn
