부산대학교 도서관

Frequency-modulated continuous-wave (FMCW) radar has become increasingly popular for contactless vital sign detection. In this article, an improved adaptive parameter variational mode decomposition (IAPVMD) algorithm is proposed for FMCW radar vital sign detection. The proposed IAPVMD algorithm can adaptively select the mode number and penalty coefficient of the variational mode decomposition (VMD) by using the energy loss rate and mode discrimination result as evaluation criteria. With the optimal decomposed parameters, the reliable and accurate reconstruction of respiration and heartbeat signals can be obtained. The experimental results show that the proposed IAPVMD algorithm achieves the estimation accuracy of respiration rate (RR) and heart rate (HR) with the mean absolute error (MAE) of 0.6 and 2.1 bpm. Compared to the existing ensemble empirical mode decomposition (EEMD), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), successive VMD (SVMD), and adaptive parameter VMD (APVMD) algorithms, the proposed IAPVMD algorithm can provide more accurate and robust RR and HR for different human subjects, different aspect angles, and distances between the radar and the human subject.