| In recent years,the research on the detection and feedback system of various physiological parameters of human body has aroused extensive interest in industry and academia.However,most of the surface electrophysiological tests on human body are related to electrocardiogram(ECG)and electroencephalogram(EEG).For surface electromyogram(sEMG),most of the studies are focused on human-computer interaction,and few of the studies are combined with sEMG to monitor human muscle state.In this thesis,a kind of stretchable flexible electrode with good conformal contact with skin is designed.By combining flexible printed circuit board and multi-features parameters algorithm,a wearable sEMG monitoring system is constructed,which realizes the monitoring of human muscle strength and fatigue and closed-loop feedback.The specific research content is as follows.Firstly,a kind of stretchable skin patch electrode is designed based on the mechanical structure of serpentine,neutral mechanical plane and air permeability design.By measuring the EMG noise signal,the feature value of the target signal in time domain and the signal-to-noise ratio(SNR)of the EMG signal,the size of the patch electrode and the distance between the electrodes were optimized to achieve the high quality acquisition of the EMG signal.Comparison of the patch electrode with three commercial electrodes shows that the contact impedance in the low frequency region(<800Hz)can be nearly 2 orders of magnitude lower than some commercial electrodes,demonstrating excellent electrical performance.At the same time,under the strain(10%～20%)caused by normal physiological activities of human body,the patch can keep close conformal contact with skin without slippage,which largely avoids signal interference caused by moving artifacts.Secondly,based on the differences of individuals,individual physiological states and exercise modes,this thesis designed a multi-features parameters extraction algorithm of sEMG signals,and used six kinds of commonly used time-domain feature values and two kinds of frequency-domain feature values to characterize the muscle strength and fatigue of muscle health indicators,and carried out the relevant muscle health status analysis research.In order to realize real-time monitoring and display,an integrated wearable sEMG monitoring system is designed,in which the flexible circuit design of multi-auxiliary circuit optimization is used to process the EMG signal,which is transmitted to PC upper computer or mobile phone for analysis and display through Bluetooth.Finally,based on the results of the systematic study,in order to eliminate the differences of individuals,individual physiological states and exercise modes and achieve real-time muscle state assessment,we selected the feature value parameter with the highest linear correlation between multiple time domain feature values and muscle strength before each exercise as the indicator parameter of muscle strength.Combined with frequency domain feature value of the rest state before exercise and of the lowest value during exercise,a simple muscle fatigue index was developed to characterize the muscle fatigue degree.At the same time,in order to realize the active feedback treatment for the monitoring results of muscle state,the possibility of active elimination of muscle fatigue assisted by electrical stimulation and hot compress was verified.In summary,a wearable surface EMG monitoring system was developed in this thesis.By systematically studying six kinds of commonly used time domain feature values and two kinds of frequency domain feature values of surface EMG signal,realtime characterization of muscle strength and muscle fatigue indicators were realized.It lays a foundation for the future application of real-time surface EMG monitoring in efficient exercise training guidance and rehabilitation evaluation. |
