Research On Human Vital Signs Based On Empirical Mode Decomposition

The safety guardianship of the elderly is the primary problem in the healthy elderly care industry and also a social problem that needs to be solved urgently at present.Detection of human cardiopulmonary signs signals including information on metabolic status and health level can accurately obtain the real-time status of the elderly,which is the first choice for health guardianship.In recent years,non-contact cardiopulmonary signs detection technology based on Frequency Modulated Continuous Wave(FMCW)radar has been widely studied and achieved satisfactory results.However,it has the problem of pose clutter,and the problem of high error in the detection results of cardiopulmonary signals in the case of human body movement interference.In order to reduce the detection error,the work in this paper is as follows:The Ensemble Empirical Mode Decomposition(EEMD)will cause modal aliasing and oscillation when the signal is decomposed.In this paper,we propose a human cardiopulmonary sign signal processing method TI-EEMD(Translation invariant Ensemble Empirical Mode Decomposition)based on EEMD and combined with translation-invariant wavelet transform.The order of singular points in the original signal is changed by multiple displacements,and the decomposed components are overall averaged to reduce modal aliasing and oscillation in the signal.The result shows that compared with the EEMD algorithm,TI-EEMD reduces the respiratory rate error of human cardiopulmonary modeling signals by 26.92%,respectively.For the pose clutter,the two situations of the human body facing the radar and back to radar are mainly discussed.When the body is facing the radar,the body movement threshold is increased to judge whether there is a large displacement of the body,so as to avoid drowning the cardiopulmonary signals by the large body movements.The result shows that compared with EEMD and EMD,the average breathing error of TI-EEMD is reduced by 5.91% and 14.34%,respectively,the average error of heartbeat is reduced by2.20% and 10.38%,respectively.When the human body is facing away from the radar,the method of distance window screening is adopted.The coherence of different range bin displacements in space is quantified by spatial phase coherence.The distance window with the highest coherence is selected for TI-EEMD vital sign extraction to reduce the interference of signals at other distances.The result shows that compared with EEMD and EMD,the average breathing error of TI-EEMD is reduced by 7.42% and 15.51%,respectively,the average error of heartbeat is reduced by 2.92% and 10.79%,respectively.As for human body movement interference,the doppler component generated by body movement is similar to cardiopulmonary Doppler.The error can be reduced by analyzing the periodicity of signal and selectively deleting the interference caused by body micro-movement.Compared with the facing radar,the average error of breathing in TI-EEMD,EEMD and EMD is further reduced by 1.79%,4.29% and 5.29%,the average error of heartbeat is further reduced by 1.60%,1.75% and 3.91%.The improved method proposed in this paper has good accuracy,and the detection performance of cardiopulmonary signs is high when the human body is facing the radar,facing away from the radar,and in the presence of body movement interference.In this paper,the data display terminal is designed to display the data of human cardiopulmonary signs in real time,which can meet the security guardianship needs of the elderly.