Radar-Based High-Accuracy Cardiac Activity Sensing

Abstract

Noncontact vital-sign telemonitoring by radar systems is applied more widely. When considering the implementation of Doppler radar for more precise extraction of cardiac physiological parameters to adapt to clinical diagnosis of heart diseases, the most open heart rate (HR) detection methods based on the periodic information are far from enough. Here, this article presents a new simple, effective, and high-accuracy settlement to maintain cardiac activity sensing comprehensively and systematically for the first time, for the estimation of beat-to-beat intervals (BBIs) and cardiac timings. We propose the decoding peak detection (DPD) method to address heartbeat peaks’ extraction problem by decoding the most likely sequence of states from the single-band frequency envelogram (FEnv) of the radar signal, thus realizing HR variability analysis. Furthermore, a hidden semi-Markov model (HSMM) is utilized to detect cardiac timings in bandpass filtered radar data, which is equivalent to positions of the R-peak and end-T-wave carried in electrocardiogram (ECG). Experimental results show that the proposed method achieves an average <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_{1}$ </tex-math></inline-formula> score of 93.19% ± 0.73% with the ECG as gold-standard, evaluated on a data set from six subjects. The accuracy of radar-based extracted BBIs is assessed by the mean relative error, which ranges from 0.51% to 1.06% by HSMM and 0.37% to 1.15% by DPD, respectively. Finally, a series of experiments are conducted to confirm the high agreement between radar signals and cardiac activities. Meanwhile, from the cardiac timings analysis by the proposed methods, we can find the advantage of radar-based detection at some specific timings compared with ECG-based, e.g., end-T-wave detection.