Vital Signs Detection in the Presence of Nonperiodic Body Movements
Didi Xu, Weihua Yu, Yufeng Wang, Mengjun Chen
Abstract
Nonperiodic body movements is one of the most challenging issues in noncontact vital sign detection. The considerable and irregular displacements of the human body could corrupt the vital sign signals, drastically reducing detection accuracy. In this article, an adaptive motion noise cancellation scheme based on frequency-modulated continuous wave (FMCW) virtual antenna array radar is proposed for real-time monitoring of vital signs with large body movements. This scheme suppresses the nonlinear noise caused by body motion and extracts accurate vital sign data. The proposed method is validated through simulation using a model of the vital sign detection system. Experiments were then carried out using a 77 GHz noncontact vital sign detection system, and the results were compared with data from a wearable device (MI6). The static experimental outcomes show that the errors in respiratory rate (RR) and heart rate (HR) are within 2 and 3 bpm, respectively. The results of exercise test, with a velocity range of 0–0.5 m/s, show that the error of RR and HR is kept within 5 bpm. The experimental results demonstrate the high efficiency of the algorithm in suppressing motion noise and accurately extracting RR and HR.