Design And Experimental Research Of Non-contact Physiological Signal Monitoring System

Heart rate signals and breathing signals reflect the health status of human cardiopulmonary function to a certain extent.In view of the aging of the population and the increasing social sub-health problems,daily monitoring of human heart rate and breathing can help human health management.The human vibration signal acquisition system can collect Ballistocardiogram signals and respiratory signals that reflect the working condition of the heart under non-contact conditions.It has the advantages of low cost and convenient operation,and it is suitable for daily monitoring in the home.This article is dedicated to developing a non-contact human physiological signal monitoring system that meets the needs of daily monitoring.Here are the main tasks done:1.Design a non-contact physiological signal monitoring device:the PVDF piezoelectric film sensor is improved into an arch structure with more uniform force and higher sensitivity.The sensor device is installed under the seat to sense the slight pressure generated by the vibration to complete the vibration signal of the human body collection;designs a charge amplification circuit and The voltage amplifying circuit amplifies the signal;the vibration signal is transmitted to the host computer software through the data acquisition card.2.Explore physiological signal extraction algorithms:Three algorithms for extracting BCG signals from original vibration signals are proposed.The first is based on the Hilbert-Huang variation(HHT)algorithm,improves the peak finding algorithm to make the modal decomposition results more accurate.The resulting BCG signnal contains five feature points,retaining more detailed features of the vibration signal;The second,based on the wavelet threshold noise reduction algorithm,by setting the threshold to remove the noise signal component,the resulting BCG signal has a significant noise reduction effect,the J peak is obvious,and the remaining details are removed;the third,the narrowband based on Butterworth filter The filtering algorithm,by setting the effective frequency domain range,the extracted BCG signal is smooth and stable.A respiration signal extraction method is studied.The integration algorithm and filtering are combined to eliminate the noise and BCG signal in the original signal.A smooth and effective respiration waveform can be obtained.3.Develop human body signal monitoring computer monitoring platform;implement all the above algorithms based on Lab VIEW software;extract the BCG signal and breathing signal from the original signal and display the waveform change;complete the real-time monitoring of heart rate and breathing rate and provide early warning when abnormal.4.Perform multiple groups of comparative experiments:use this system and oximeter to monitor the heart rate of the subject at the same time and the average error of the heart rate is 2.013%;perform rhythm breathing experiments on the subjects and compare the results with the set breaths Rate comparison,the average heart rate error is 4.88%.In addition,the experiment explored the BCG signal changes during exercise,eating,etc.and concluded that the peak value of the signal was positively related to the cardiac stroke output.The non-contact human physiological signal monitoring system developed in this paper can perform real-time and long-term monitoring of physiological signals.It has good practicability.