摘要
In order to detect and assess the muscle fatigue state with the surface electromyography(sEMG) characteristic parameters,this paper carried out a series of isometric contraction experiments to induce the fatigue on the forearm muscles from four subjects,and recorded the sEMG signals of the flexor carpi ulnaris.sEMG's median frequency(MDF) and mean frequency(MF) were extracted by short term Fourier transform(STFT),and the root mean square(RMS) of wavelet coefficients in the frequency band of 5—45 Hz was obtained by continuous wavelet transform(CWT).The results demonstrate that both MDF and MF show downward trends within 1 min; however,RMS shows an upward trend within the same time.The three parameters are closely correlated with absolute values of mean correlation coefficients greater than 0.8.It is suggested that the three parameters above can be used as reliable indicators to evaluate the level of muscle fatigue during isometric contractions.
In order to detect and assess the muscle fatigue state with the surface electromyography（sEMG） characteristic parameters,this paper carried out a series of isometric contraction experiments to induce the fatigue on the forearm muscles from four subjects,and recorded the sEMG signals of the flexor carpi ulnaris.sEMG’s median frequency（MDF） and mean frequency（MF） were extracted by short term Fourier transform（STFT）,and the root mean square（RMS） of wavelet coefficients in the frequency band of 5—45 Hz was obtained by continuous wavelet transform（CWT）.The results demonstrate that both MDF and MF show downward trends within 1 min; however,RMS shows an upward trend within the same time.The three parameters are closely correlated with absolute values of mean correlation coefficients greater than 0.8.It is suggested that the three parameters above can be used as reliable indicators to evaluate the level of muscle fatigue during isometric contractions.
基金
Supported by the National Natural Science Foundation of China(No.81222021 and No.31011130042)
the National Key Technology R&D Program of the Ministry of Science and Technology of China(No.2012BAI34B02)
关键词
表面肌电图
肌肉疲劳
信号特征
收缩
前臂
平均频率
连续小波变换
傅立叶变换
muscle fatigue； isometric contraction； time-frequency spectrum analysis； median frequency； mean frequency； root mean square； correlation；
