Research On Detection Of Vital Signs Signal Based On Millimeter Wave Radar

Heartbeat and breathing(respiration)are important vital signs of the human body.The detection methods include electrocardiograph(ECG)and photo plethysmography(PPG).Both of the detection methods are contact-type,which have great limitations in detecting signs of patients with severe infections and those with severe burns.In order to meet the new demands,the research of non-contact vital signs detection technology has gotten great attention.Due to the advantages such as wide bandwidth,marrow beam,high resolution,small and portable etc.,millimeter wave radar has great potential in health care field.In this thesis,the movement on the surface of human chest wall by breathing and heartbeat can be detected by millimeter wave radar.By further analyzing echo signals,breathing and heart rate can be extracted.This thesis will be focused on the research of millimeter wave radar's detection of vital signs.Firstly,the principle of detecting vital sign signals by millimeter is introduced in detail,and signal detection and flow is established,including signal acquisition,signal preprocessing,and signal rate estimation.In signal preprocessing,Radar echo front-end signal processing algorithm has been verified by building the model of the radar's echo signal.Then,the vital sign rate estimation is performed on the phase signal.in order to reduce the influence of background noise during the actual signal test,the mean filtering algorithm will be used in this thesis to smooth the front-end signal.After that,the short-time Fourier transform(STFT),variational modal analysis(VMD)and sliding window-MUSIC algorithm will be used to analyze the temporal frequency of breathing and heartbeat signals.For the STFT algorithm,we choose an appropriate signal observation window period to balance the contradiction between the frequency resolution and the ability to local variation resolution.For the sliding window-MUSIC algorithm,this thesis adopts the sliding window algorithm to enhance the real-time performance of the MUSIC algorithm,and the detection accuracy of a single person's vital sign signal reaches 93.3% within a period of time(190s).By comparing and analyzing the processing results of the three algorithms,the STFT algorithm is more suitable for situations where the signal spectrum complexity is low(such as the frequency estimation of the respiratory signal),and VMD algorithm performs well in the timedomain signal decomposition,under the condition that cardiopulmonary signal is stable.Compared with the other two methods,the sliding window-music algorithm has strong anti-harmonic interference ability,high frequency resolution and high accuracy.Finally,this thesis uses sliding window-MUSIC algorithm to explore the possibility of detecting vital signs signals in the scene where the radar and the human body are at different angles,in the scene of lying down and standing walking,and in the scene of two people sitting.By analyzing the real-time test results,the algorithm can reliably detect vital sign signals in a relatively static scene,but the algorithm reliability is weak in moving scenes.