Non-contact Detection And Processing Of Human Vital Signal Based On IR-UWB Radar

In recent years,personal medical and health issues have become a hot topic in society.People’s concern for their own physical health status is increasing year by year,and there is a wider demand for applications that can continuously record physical health status.Therefore,it can be seen that the non-contact detection of human vital signal,and the ability to continuously perceive the direction of human health status,has broad application prospects.Continuous monitoring of vital signs,such as respiration and heartbeat,plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient.Sensing vital signs can be categorized into: contact-based techniques and non-contact based techniques.Conventional clinical methods of detecting these vital signs require the use of contact sensors,which may not be practical for long duration monitoring and less convenient for repeatable measurements.On the other hand,wireless vital signs detection using Impulse Radio-Ultra Wide Band（IR-UWB）radars has the distinct advantage of not requiring the attachment of electrodes to the subject’s body and hence not constraining the movement of the person,and reduces skin irritation and cross-infection diseases risks of.The work of this thesis revolves around the non-contact detection and processing of human vital signal by IR-UWB radar.The main work contents and innovations include:（1）A background noise removal method and an improved two-layer Ensemble Empirical Mode Decomposition（EEMD）algorithm are proposed.According to the characteristics of IR-UWB radar detection echo signal through the wall,it is proposed to use the background noise elimination method in the preprocessing stage of radar echo signal,which can reduce the echo signal interference of fixed objects in the environment.On the basis of the previous one,a modified two-layer EEMD method which is more suitable for through-wall detection scenarios is proposed.（2）The echo signal model is established,and the algorithm proposed in this thesis is simulated and verified.Different environmental noise signal-to-noise ratios are set in the simulation to generate simulated echo signals,and then the modified two-layer EEMD method is used to analyze and process the echo signals.The simulation results verify the feasibility of the modified two-layer EEMD method.（3）Carry out actual test verification,and analyze and display the experimental results.Several groups of control experiments were carried out in common usage scenarios,and it was concluded that the detection distance of 1m in an indoor open environment is more suitable for radar to detect human vital signal through walls.Comparing the performance with the commonly used traditional processing algorithms,the results show that the modified two-layer EEMD method has more advantages in practical use scenarios.Carrying out many experiments in the best use scenario,the average respiration estimation error of the modified two-layer EEMD method in the actual test is 1.74%,and the average heartbeat estimation error is 3.89%.