An innovative approach for FMCW radar vital sign monitoring with removal of respiratory harmonics

Frequency Modulated Continuous Wave (FMCW) radar shows broad research potential in monitoring vital signs. However, the harmonic components generated by the human respiratory process overlap with the frequency band of the heartbeat signal, posing challenges to precisely monitoring the heartbeat signal. To address this issue, this paper introduces the singular spectrum analysis method, which accurately identifies and removes respiratory harmonics by adding a sine signal with the same frequency as the respiratory harmonics to the original time series. Furthermore, the paper introduces energy entropy and the Pearson correlation coefficient to comprehensively decompose physiological signals to optimize the traditional variational mode decomposition algorithm, proposing the EE-VMD and PCC-VMD algorithms. Experimental results demonstrate that the SNR increased, and the accuracy of measuring respiratory rate and heartbeat rate has significantly improved. The results presented in this paper not only advance theoretical methodologies for the monitoring of human vital signs but also underscore the practical applicability of FMCW radar in this domain.