Research On Biological State Analysis System Based On Multiple Physiological Signals

With the development of biometric technology,how to effectively recognize the biological state has gradually become a research hotspot in the field of biological state analysis.The emergence of the biological status analysis system replaces the traditional manual identification method and realizes automatic identification and analysis.However,existing biological state analysis systems mostly use a single signal source for biological state recognition,which has problems such as low recognition accuracy and greater environmental interference.Therefore,it is of great significance to design a real-time,efficient,and portable biological status recognition system.The main work of this paper is as follows:(1)A physiological signal processing method based on the fusion of multiple physiological data is proposed.First of all,according to the time-frequency characteristics of the signal,the signal noise is effectively reduced by filtering,wavelet noise reduction,and other methods;then,considering the system real-time and signal feature dynamic extraction requirements,the time domain analysis method is used to analyze the electromyographic signals and heart signals involved in the system.Feature extraction of multiple physiological signals,such as electrical signals and muscle deformation signals,has been carried out to strengthen the differences of various physiological states;finally,the feature layer fusion method is introduced for data fusion processing.The results show that the method proposed in this paper has a good processing effect and provide an effective method for further state recognition.(2)Design a portable wireless multi-physiological signal acquisition and analysis system.First,according to the characteristics of physiological signals,considering its power frequency interference,nonlinearity,and other factors,the biological front-end processing circuit is designed to achieve high dynamics and low distortion to achieve signal acquisition;then,based on the design requirements of low power consumption and high rate wireless transmission A wireless networking solution based on the integration of Bluetooth MESH low-speed network and WIFI high-speed network;finally,a software system was built based on the QT platform to realize the online platform processing of multiple physiological signals.(3)Conduct experimental design and analysis based on multiple physiological signals.Aiming at the problem of gesture recognition combined with multiple recognition models,an experimental scheme based on the fusion of three heterogeneous data of electromyography,muscle deformation,and posture was designed;for the problem of physiological state recognition,an experimental scheme based on two heterogeneous data of electrocardiogram and body temperature signal was designed.The experimental plan,combined with the state recognition algorithm,carried out the biological state recognition in different motion states.The experimental results show that the biological state recognition method used in this paper has a good recognition effect.