Design And Development Of The High-density Surface Electromyogram Acquisition System

Surface Electromyography(s EMG)signal is the most comprehensive and widely studied signal source in muscle group control interface.And its research level directly affects the quality of life of amputees.In recent years,with the deepening of its research,people also began to pay attention to the high-density s EMG,in order to obtain more comprehensive spatial distribution characteristics and high-throughput physiological signals of s EMG.At present,only a few companies in the world have launched acquisition equipment with high-density(HD)s EMG collection capability.The biggest problem of this kind of equipment is that although it has the ability of HD signal acquisition,it is not portable enough,and the price is expensive,which is not friendly to large-scale experiments of in vivo measurement.Based on the above situation,this paper proposed and developed a set of low-cost,modular,high-performance,portable and high-density s EMG acquisition system.In this paper,after the detailed demand analysis of HD-s EMG system,a set of layered modular acquisition system was designed,which includes an expandable,modular high-density s EMG acquisition equipment and a cross platform,multi-functional upper computer software.In this paper,the hardware equipment,upper computer software and communication between various equipment and synchronization of each equipment were tested and verified.Moreover,further optimization work was carried out.Based on the analysis of the common noise characteristics of EMG signal,this paper also modified the real-time digital filter algorithm,and improved the real-time digital filter algorithm.This was needed to achieve realtime acquisition and processing of 128-channel 4k Hz sampling frequency16-bit precision with only a ARM Cortex-M4 microcontroller(MCU).After testing the single channel and multi-channel signal data,the inverse solution algorithm of the Motor Unit Action Potential train(MUAPt)was realized and tested by using this device.After that,an experiment of classifying the gesture and an experiment of estimating the grade of power of grip were launched.The experimental results show that the system can achieve the comparable mechanical index of similar equipment for HDs EMG signal acquisition,and meet the requirements of inverse solution of MUAPt.