关键词: 毫米波雷达, 经验小波变换, 生命体征, 心率变异性, 麻雀搜索算法

Abstract: In response to problems such as low accuracy and poor real -time detection of existing radar non-contact vital signs detection, a human vital signs detection algorithm based on frequency modulated continuous wave radar was proposed. The vital signs signal was first obtained through the millimeter wave radar, and then the adaptive decomposition and reconstruction of the vital signs signal were achieved using the improved experience wavelet transformation method. The best value of the spectrum division line was found by introducing the Sparrow Search Algorithm(SSA) and the Fuzzy Entropy(FE), and subsequently, the heart rate and respiratory rate were calculated using the estimation algorithm with improved frequency interpolation. The superiority and robustness of the algorithm in this article were verified through comparative experiments with a medical critical care monitor.The experimental results show that compared with the Wavelet Transform(WT) algorithm 、Complementary Ensemble Empirical Mode Decomposition (CEEMD) algorithm and Variational Mode Decomposition(VMD) algorithm, The Mean Square Error (MSE) was reduced by 77.65, 27.25, and 21.05, The Mean Absolute Percentage (MAPE) was reduced by 7.33, 4.33 and 3.42 percentage pionts, and the real-time performance was improved by 0.72s, 16.74s, and 1.87s. At the same time, the algorithm of this article also achieved detection of Heart Rate Variability (HRV).

Key words: millimeter-wave radar, empirical wavelet transform, vital signs, heart rate variability, Sparrow search algorithm