Research Of Portable Surface EMG Signal Processing System Based On DSP

Surface electromyography(sEMG) is a muscle in the excited state of the collected by the movement unit generated by the action potential sequence(MUAPT) superimposed on the skin surface of the human body, which belongs to the weak signal. Surface electromyography(s EMG)research field mainly for surface EMG signal of human action recognition and surface signal decomposition research hot spot. The former is mainly used in the field of intelligent prosthetic control and sign language recognition, through the pattern recognition to extract independent consciousness of the human body to achieve the control mechanism, and the latter is mainly from the surface EMG signal extraction motor unit action potentials(MUAP) waveform information and control mechanism of neuromuscular system, and as a basis for the diagnosis of the disease.Surface muscle fatigue detection in kinematics, rehabilitation medicine and muscle damage diagnosis and other fields have a wide range of applications. Surface muscle fatigue test can provide people reliable analytical data to determine which state human muscle, so as to rehabilitation assessment, physical exercise and smart analysis provides an effective method of analysis, electromyography fatigue detection for its non-invasive, objective and convenience become reliable tool for people to study the surface EMG, So that people in the full understanding of the state of muscle fatigue and effectively avoid the damage caused by muscle fatigue.This paper focuses on the electromyographic fatigue detection algorithm in DSP implementation, first in MATLAB verify the algorithm’s effectiveness, then through the DSP using the same algorithm and obtain the MPF values and comparison of MATLAB and DSP processing collected EMG signals, obtained under different processing error inspection certificate transplantation to the effectiveness of the algorithm in the DSP, and through the program migration, program by the Starterware migrate to the DSP/BIOS system, improving algorithm to deal with the real time, finally through the visual interface using households on their muscles state intuitive understanding, helpful for researchers to further analysis of the electromyographic fatigue, for the system ultimately to portable may provide.The EMG analysis of real-time requirements are relatively high, this paper in the aspects of hardware and software improve real-time performance of the whole system, is more commonly used muscle fatigue analysis method can well improve the analysis in real time. And the analysis of muscle fatigue can be divided into different intervals by the test time, the muscle fatigue in each period of time were observed, to provide an effective method for the analysis of muscle fatigue.