Design And Application Of Flexible Nano Wearable Pulse Sensor Based On P(VDF-TRFE)

Pulse signal contains abundant physiological and pathological information of human body,which has been applied in many fields,such as emotion recognition and analysis based on pulse.The traditional pulse signal detection methods include photoplethysmography(also known as PPG method)and pressure detection.Among them,PPG method has limited detection accuracy and is greatly affected by daily light changes.Pressure detection method mostly uses rigid structure,such as piezoelectric ceramic sensor,which has poor flexibility,wearability and comfort.Therefore,it has important scientific significance and clinical needs to study the detection and analysis of pulse wave signal.Firstly,in view of the shortcomings of the pulse wave detection technology mentioned above,a design scheme of a flexible wearable nano piezoelectric pulse sensor based on poly(vinylidene fluoride trifluoroethylene)(P(VDF-Tr FE))/GR(graphene)is proposed.A set of horizontal high-voltage electrospinning optimization experimental platform is built,which is based on the improvement of the original vertical high-voltage electrospinning equipment in the laboratory.Based on this experimental platform,A method for preparing P(VDF-Tr FE)/Graphene(GR)composite nanofiber films by electrospinning was proposed,and the characteristics and piezoelectric properties of the nanofibers were studied.The author has prepared P(VDF-TRFE)/GR composite nanofiber films with different graphene components,and observed the morphological and structural characteristics of the nanofibers of different film samples by scanning electron microscope(SEM).Observed by scanning electron microscope,it is found that the nanofibers of the composite film prepared by adding appropriate amount of graphene are more orderly,and the pore uniformity is enhanced,the fiber diameter is reduced and the distribution is more uniform,and the flexibility of the film was better.Secondly,a flexible piezoelectric sensor with composite film as functional layer was designed and fabricated,and its electrical response output test and capacitance charging test were carried out.It was found that with the increase of graphene concentration,the open circuit output voltage,short circuit output current and capacitor charging efficiency of the flexible piezoelectric sensor were significantly improved,including P(VDF-Tr FE)/GR flexible piezoelectric sensor sample containing0.2% graphene Compared with pure P(VDF-Tr FE),the open circuit output voltage and short-circuit output current of P(VDF-Tr FE)are increased by about 2.0 and 2.2 times respectively.For the P(VDF-Tr FE)/GR flexible piezoelectric sensor with 0.2% graphene,the back-end conditioning circuit module of P(VDF-Tr FE)/GR flexible piezoelectric sensor is designed.The module is composed of charge amplifier,voltage amplifier and bias circuit.After amplifying the radial artery pulse signal obtained by piezoelectric sensor,the module transmits it to the acquisition module of Lab VIEW through usb-6008 data acquisition card.Finally,the final acquisition,filtering and storage of pulse signal are realized on Lab VIEW platform.The denoising method of pulse signal is studied.In this paper,an improved adjustable wavelet threshold function is proposed to denoise the pulse signal.The experimental results show that the improved wavelet threshold function can get better performance indexes of mean square error and signal-to-noise ratio than several common wavelet threshold functions introduced in this paper.The method of emotion classification and recognition based on pulse wave signal is studied.Based on the characteristics of denoised pulse signal,the main peak of pulse is accurately detected by differential threshold method,and a total of 25 feature parameters are extracted,including 5time-domain features and 20 discrete small baud parameters.SVM algorithm based on grid search algorithm(GSA)for parameter optimization is used to classify and recognize the emotion of pulse wave signal.The pulse wave data set used in this article includes 300 cases of pulse wave signals in the public pulse emotion research database about 100 cases of pulse wave signals in calm,happy,and sad emotional states.The P(VDF-TRFE)/GR flexible piezoelectric pulse sensor developed in this article is collected of the 75 cases,there were 25 cases of pulse wave signals in calm,happy,and sad emotional states.Using the GSA-SVM algorithm,three two-category emotion recognition models based on pulse signals,which are classified as calm and happy,calm and sad,and happy and sad,are constructed respectively.The research results show that the trained emotion recognition model has a recognition rate of 84.02% for emotions in a calm and happy state,80% of emotions in a calm and sad state,and 88% of emotions in a happy and sad state.The results of the research show that the proposed method for pulse detection and analysis based on the P(VDF-TRFE)/GR composite film-based flexible nano-piezoelectric sensor has certain feasibility and advancement.This method is useful in pulse signal detection and emotion analysis And other fields have certain application prospects.