Non-Contact Vital Signs Detection Using mm-Wave Radar During Random Body Movements

Vital signs such as heartbeat and respiration signals are significant indicators for health care and clinical applications. Non-contact vital signs detection via mm-wave radar has attracted more attention due to more comfortable experience and lower burden. However, the non-contact heartbeat and respiration signals detection with random body movements is more challenging. In this paper, we propose a general framework to address this problem. It is termed DRSEPK and consists of signal decomposition and reconstruction, spectrum estimation and spectral peak tracking. Signal decomposition and reconstruction is applied for denoising and reconstructing cleaned signal. Spectrum estimation aims to get high-resolution frequency spectrum. The spectral peak tracking can select correct spectral peaks corresponding to breath rate (BR) and heartbeat rate (HR). Experiments are conducted using frequency modulated continuous wave (FMCW) radar on ten subjects who are typing on a laptop. The results show that the DRSEPK framework has high estimation accuracy and is reliable for non-contact vital signs detection during random body movements.