Detection of an increase in EMG regularity during fatiguing contractions  

疲劳收缩过程中EMG信号规则度增加的检测(英文)

作　　者：陈伟婷[1] 曹桂涛[1] 王志中[2] 

机构地区：[1]华东师范大学软件学院,上海200062 [2]上海交通大学生物医学工程系,上海200240

出　　处：《Journal of Southeast University(English Edition)》2010年第4期541-545,共5页东南大学学报（英文版）

基　　金：The National Basic Research Program of China(973Program)(No.2005CB724303);the Natural Science Foundation of Shanghai(No.09ZR1409600);the Shanghai Leading Academic Discipline Project(No.B412)

摘　　要：The changes in the evolvement patterns of surface electromyography（EMG）signals during both static and dynamic fatiguing contractions are studied.The main finding is that the EMG signal tends to be more and more regular as muscle fatigues.An increase in the summation of all the regular evolvement patterns denoted by Dreg reflects such a tendency.Compared with traditional measurements,Dreg shows less variability among subjects when characterizing a fatigue process.In addition,the calculation of Dreg in the time domain is free from the restrictions disturbing those of spectral parameters.The detection of an increase in the EMG regularity not only proposes a new and easy way to inspect changes in EMG during the fatigue process,but also provides strong supports to estimate muscle fatigue by means of nonlinear analysis methods such as entropy and complexity measures.The detection method of signal regularity can also be applied to other physiological signals.研究了肌肉静态及动态收缩过程中表面EMG信号演化模式的变化,发现了疲劳进程中肌电信号趋于规则性变化的规律,信号的所有规则性演化模式之和(以Dreg表示)的增加反映了该规律.与传统的疲劳指标相比,Dreg在刻画不同人体的肌肉疲劳时变异性更小.此外,基于时域的Dreg的计算可以避免传统频域指标的使用局限性.EMG信号规则度增加的发现,不仅为检测疲劳进程中EMG信号的变化提供了一种新的简易方法,更为以往工作中通过非线性指标(包括熵和复杂度等)来评估肌肉疲劳提供了有力的证据.介绍的信号规则度检测方法同样适用于其他生理电信号.

关 键 词：muscle fatigue surface electromyography（EMG） REGULARITY 

分 类 号：R318[医药卫生—生物医学工程] TP391[医药卫生—基础医学]