Research On Eight-channel Electromyography Detection System

With the gradual increase of the aging population in China,the number of stroke patients has also increased day by day.In the next 30 years,there will be a large number of patients with hemiplegia.It will become more and more urgent for the study on the therapies of paraplegia and hemiplegia.In the early stage,our research team designed the eight-channel microelectronic electromyographic bridge(EMGB)prototype,using functional electrical stimulation(FES)to help patients with spinal cord injury or stroke rehabilitation.However,the patients with limb paralysis have different causes,degree of disease and length of injury recovery,resulting in different treatment and subsequent recovery status.Therefore,this paper is to develop a surface electromyography applied to eight channels.The instrument can collect and amplify the myoelectric signal of the body surface,and observe the physiological state of the human muscles and nerves by using the time-frequency domain index to achieve the auxiliary evaluation of the rehabilitation situation.In addition,the muscles reaching fatigue during the rehabilitation process will also affect the subsequent treatment effect.On the basis of the surface electromyograph,this topic proposes the idea of constructing a muscle fatigue monitoring system,and detects the fatigue state of the muscle while performing the electromyographic stimulation,to improve the effect of neuromuscular electrical stimulation to a certain extent.Firstly,the subject investigates the physiological basis of the EMG signal,and explores the mechanism,main features and time-frequency domain characteristics.Based on this,this paper designs the overall structure of the surface electromyography signal detector and analyzes the requirements of each component module.Then,the subject is designed for the realization of the hardware circuit and software system for the eight-channel surface electromyography,including the acquisition and transmission of myoelectric signals,real-time display of myoelectric waveforms,storage replay and spectrum analysis and time-frequency domain eigenvalue analysis in discrete analysis modules.Secondly,the subject further explores the role of surface electromyography in the evaluation of muscle fatigue,and designs a muscle fatigue monitoring system to monitor the state of muscle fatigue during rehabilitation training to facilitate optimal rehabilitation.Finally,the subject tests the system and analyzes the performance.The result shows that the surface electromyograph can realize the display and spectrum analysis of the EMG signal,and can promptly remind the patient to stop the experiment when the state of muscle fatigue is reached.