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 regu...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.展开更多
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)
文摘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.
