Research On Human Respiratory Signal Extraction Based On MIMO Technology

Non-contact human respiratory detection has attracted more and more attention because of its advantages such as comfort and safety.The respiratory detection system based on Fresnel area model can detect human respiration by using commercial Wi-Fi and other wireless communication devices.It is one of the most promising schemes in recent years because it is cheap and easy to popularize.However,most existing respiratory detection systems have fixed parameters,such as those based on commercial Wi-Fi devices.They have a large detection blind area,which greatly limits the practical application scenarios.Therefore,it is very important to study how to eliminate the detection blind area and improve the effect of respiratory detection.Aiming at the problem of how to reduce the detection blind area of the respiratory detection system,this paper studied from the aspects of adaptive parameters and multiple input multiple output(MIMO)technology,and completed the design of the MIMO adaptive respiratory detection system.The details are as follows:1.In this paper,a design method of adaptive parameter respiratory detection system is proposed.The mathematical relationship between system parameters and respiratory detection effect is established to help the system adjust parameters when the position of human body is known.Then a method to evaluate the respiratory detection ability of the system is proposed which provides a theoretical basis for the parameter adjustment of the adaptive parameter system when the position of human body is unknown.The simulation results show that the respiratory detection rate of the adaptive parameter system is 99.4%,while that of the fixed parameter system is only 75.8%.The adaptive parameters effectively reduce the detection blind area of the system.2.A method is proposed to extend the adaptive parameter respiratory detection system of simple input simple output(SISO)to MIMO system,which enhances the respiratory detection capability of the system and reduces the number of system parameter adjustment.On the basis of SISO system,this paper gradually adds transceiver antenna and keeps the original antenna position unchanged to obtain a better antenna distribution position and greatly reduces the amount of calculation.The simulation results show that the respiration detection rate of the MIMO adaptive parameter system is 99.6%and the detection blind area is basically eliminated.3.A 2 X 2 MIMO adaptive parameter respiratory detection system was built based on USRP equipment.The respiratory detection rate of MIMO adaptive parameter system is compared with that of SISO fixed parameter system.The experimental results show that the respiration detection rate of MIMO adaptive parameter system is 96%,while that of SISO fixed parameter system is only 76%.Obviously the former have better respiratory detection ability.4.A wavelet denoising method with improved threshold function is proposed to denoise respiratory signals.Aiming at the feature extraction of respiratory signals,a method of respiration rate extraction based on the rising/falling edge of respiratory signals and a method of respiration depth calculation are proposed,which have a good processing effect on irregular respiratory signals.