Realization On Extracting Technology Of Heartbeat And Respiration Based On UWB Bioradar

With the rapid development of bioradar technology,the demand for this technology in various fields is also increasing.Ultra-wideband bioradar technology is widely used at present,and ultra-wideband bioradar technology has high precision,strong anti-interference ability,and low energy consumption.Since the echo signal contains a large amount of environmental noise,and the human body's heartbeat,breathing and other vital signs signal are relatively weak,the noise in the echo signal received by the radar device will submerge the vital sign signal.In order to more accurately collect the life information of the human body,the denoising processing of the echo signal and the separation of the heartbeat and respiration of the echo signal are very important.Emphasis is placed on the extracting technology of heartbeat and respiration.In this work the working principle of ultra-wideband bioradar is analyzed.Through the calculation of relevant parameters and indicators of the radar system,suitable antennas,power amplifiers,low noise amplifiers,analog-to-digital converters and other devices are selected,and the PCB layout is designed.The bioradar hardware system was studied.The algorithm for processing the echo signal of bioradar was deeply studied.The echo signal was modeled by MATLAB.The simulation results verify the effectiveness of the algorithm.Emphasis is placed on the denoising and separating of echo signal.Using the empirical mode decomposition algorithm to decompose the echo signal into a finite number of intrinsic modal functions,the high frequency part and the low frequency part of the signal are initially separated,and the energy law and autocorrelation function are applied to judge the proportion of the noise or useful signal in the intrinsic modal function,analyzing the property of the intrinsic modal function,and use a similar wavelet soft thresholding method to denoise the intrinsic mode function with a relatively large amount of noise,and use the processed signal of the intrinsic modal function performs signal reconstruction and finally the denoised echo signal is obtained.MATLAB simulation shows that the EMD algorithm improves the SNR of the signal from-10 dB to 13.23 dB,and the mean square error of the echo signal is 0.0012.This proves that the algorithm can effectively improve the signal to noise ratio of the signal and guarantee low signal distortion.The de-noised echo signal was separated using the least mean square algorithm.Firstly,the bioradar system is used to collect the heartbeat signal of the human body holding the breath,and the heartbeat signal is denoised by the empirical mode decomposition algorithm,which is used as the expected signal of the minimum mean square algorithm;the mixed signal processed by the EMD algorithm contains(Heartbeat and respiration)as the input signal of the minimum mean square algorithm;After many times iterations,the heartbeat and respiratory signal were successfully separated,and the signal-to-noise ratios of the separated heartbeat and respiratory signal were 12.37 dB and 11.59 dB,respectively.1.247 Hz,0.252 Hz,the frequency error relative to the modeling signal was 0.3%,0.2%,and the mean square error was 0.0031,0.0026,respectively.Finally,the respiratory and heartbeat echo signal of healthy adults were collected through experiments,and the echo signal were processed using the algorithm studied in this paper.In order to verify the experimental results,multiple sets of experiments were conducted in this paper,and the separated respiratory signal and set frequencies were performed.In comparison,the detected heartbeat signal and the ECG signal are compared to obtain a high correlation coefficient between the seven groups of heartbeat signal and the ECG signal.The frequency error of the relative ECG signal is within the calibration error range.