Extraction of Vital Sign Based on PE and ICEEMDAN for UWB Radar

Ultrawideband (UWB) radar enables noninvasive detection of human vital signals without any electrodes or sensors touching the human body. In order to eliminate and reduce the clutter interference in the vital signal when performing life search and rescue, a UWB radar vital sign extraction method based on the combination of permutation entropy (PE) and improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is proposed for this problem. Based on the slow time series echo characteristics of the received signal echo matrix, the distance gates are determined using PE values; in addition, the selected slow time series are reconstructed and denoised using ICEEMDAN, and the frequencies of the reconstructed respiratory and heartbeat signals are extracted using fast Fourier transform (FFT); finally, a total of 15 sets of experimental data at three distances are collected from five volunteers, respectively, for experimental validation, and the experimental analysis The results showed that the proposed algorithm detected an average error of 0.0093 m for distance, 0.0127 Hz for respiration frequency and 0.036 Hz for heartbeat frequency. The proposed algorithm has the advantages of being resistant to environmental interference, adaptive and reliable, and can accurately locate the target location and extract the frequencies of respiration and heartbeat signals.