Experimental Study On The Skeletal Muscle Functional Statues Based On The Nonlinear Dynamic SEMG Signal Analysis

sEMG signal is the sum of bioelectrical activities that recorded from the working muscle by the surface electrodes.Because, During the maintenance of muscle contraction, the sEMG signal changes reflect the changing metabolic status of the working muscle, and readily observable in the absence of any decline in the muscle 's mechanical output,sEMG signal analysis is always recognized as an effective method of evaluating the muscle fatigue in time. The purpose of this study was to observe the patterns and characteristics of the signal changes by calculating the signal complexity and entropy; to compare the validity difference between nonlinear and linear method; and at last to construct the working mechanism of neuro-muscular system during development of muscle fatigue. Four experiments were conducted and 40 male healthy subjects volunteered for this study . sEMG signal were recorded from both lumbar muscle and upper limb triceps by Multiple Physiological System and PcLab Bioelectrical Signal Processing System during isometric and dynamic fatiguing contractions and signal complexity ,entropy, iEMG and mean power frequency were calculated by nonlinear and linear power spectrum method afterwards. The results of experiment one showed that sEMG signal is nonlinear and chaos dynamics system for the patterns of signal wereamong the periodic and random signal. The results of experiment two and three showed that Kolmogorov entropy^ inhibit word complexity and Lempel-Ziv complexity of 90%-100% subjects declined linearly with the duration of static contractions and the times of dynamic contractions. The slopes of decline were high related to the muscle functional level; In experiment four, all of the indexes analysised declined linearly in the condition of isometric contractions with linear analysis is betteT than nonlinear one, while the latter becomes better in the condition of dynamic contractions than that in the time domain linear analysis. The correlation between normalized Lempel-Ziv complexity and performance of dynamic muscle work is the highest among all indexes ,this later result suggested that normalized Lempel-Ziv complexity can be used to predict dynamic muscle activities valuably. Our results seemed to suggested the synchronization activities of motor units may be one of the important mechanisms that controling muscle woTk during exercise.