Stroke Upper Limb Muscle Fatigue Monitoring System Design Based On SEMG

According to statistics,the number of stroke patients in China is 2 million,the incidence is as high as 9%,and the rate of disability is over 70%.At the same time,stroke patients have to be protected against two recurrences,etc.The main treatment for stroke patients in China is later rehabilitation training.However,most of the patients with stroke will suffer from central nervous system injury,which can not be timely feedback to the fatigue state of the rehabilitation trainers,which is likely to cause two times of injury.Surface electromyography(surface electromyography,sEMG)can reflect the physiological information of human muscles in real time.It is a physiological electrical signal that is born on the surface of the skin.At present,there is no accepted standard database for sEMG,so we can see that the technology of sEMG acquisition and feature analysis is not mature enough to be applied to the analysis of human muscle physiological state.In view of the present situation,Combined with our hospital rehabilitation robotics laboratory of A2-arm intelligent feedback training system,I began to try to study the relationship between surface electromyography and upper limb muscle fatigue.The main work of this article includes:1.I design a portable electromyography fatigue monitoring and analysis system,including initial body surface electromyography signal acquisition,amplification and filtering module,A/D conversion,microprocessor signal analysis and processing,wireless WIFI transmission module and so on.2.I design a host computer processing system based on Android system intelligent machine,and store and display the body surface EMG signals collected by the lower machine to store,display,monitor fatigue and so on.3.I constructed the surface electromyography signal processing model,analyzed the relationship between the surface electromyography signal and the upper limb muscle fatigue in the time domain and the frequency domain characteristics,and explored the accurate measurement of the upper limb muscle fatigue based on the surface electromyography signal.4.Test and analysis of development of monitoring system,the initial sEMG for patients with upper limb stroke through the surface EMG signal acquisition system,signal processing for the later,again through the WIFI transmission to the intelligent data analysis in Android mobile phone,man-machine interface,real-time feedback to inform the muscle fatigue degree of rehabilitation of patients with stroke.