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Vital signs such as heartbeat and respiration signals are important 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 motion 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 used 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 on ten subjects using frequency modulated continuous wave (FMCW) radar and the subjects are typing on a laptop. The result shows that the DRSEPK framework has high estimation accuracy and is robust to random body motion.

Non-Contact Vital Signs Detection Using mm-Wave Radar During Random Body Movements Luyao Liu, Sen Zhang, Wendong Xiao