Human presence detection and heart rate estimation algorithm based on millimeter-wave radar

Millimeter-wave radar, with advantages such as non-contact penetration detection and privacy protection, has become a promising solution for unobtrusive monitoring in the field of smart elderly care. To solve the problem of whether there are human body in the elderly care scene, this study proposed a method for judging the presence of a human body based on adaptive dual thresholds to reduce invalid vital sign detection in an empty environment. This method used a low-frequency energy ratio as the core judgment basis. It combined adaptive thresholds to accurately judge the presence of human targets, effectively reducing false detections caused by background interference. In addition, given the defect that variational mode extraction (VME) needs to rely on manual parameter adjustment based on empirical values, the crown porcupine optimization (CPO) algorithm is introduced to optimize the VME parameters adaptively, and the optimized VME is used to reconstruct the heartbeat signal to improve the signal purity. Then, the multiple signal classification (MUSIC) algorithm was used for spectrum analysis to improve the accuracy of heart rate estimation. The results show that in the experimental judgment of personnel, the miss rate in the case of personnel presence is 2.2%, and the false alarm rate in the case of no personnel is only 3.2%; the root mean square error and mean absolute error of the proposed heart rate (HR) estimation method are reduced by 4.4 beat per minute and 3.05 beat per minute respectively compared with the traditional VME, verifying its excellence.