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This paper presents a novel algorithm for the estimation of heart rate variability (HRV) features using 24-GHz continuous-wave Doppler radar with quadrature architecture. The proposed algorithm combines frequency and time domain analysis for high-accuracy estimation of beat-to-beat intervals (BBIs). Initially, band pass filtered in-phase (I) and quadrature (Q) radar components are fused into a single combined signal that contains information on the heartbeats. Its frequency domain analysis is used for coarse heart rate estimation. At the same time, the combined signal is processed using a filter bank containing narrowband band pass filters with different center frequencies. One of the band pass filter outputs is selected as the valid output based on the coarse heart rate estimation. Zero crossings in the resulting filter bank output signal represent heartbeats that are used to extract the BBIs. Finally, four HRV features are calculated from the BBIs. The algorithm is tested on real data obtained from recordings on ten human subjects. The mean relative error of extracted BBIs compared to electrocardiogram (ECG) measurement is in the 1.02–2.07% range. Furthermore, two time-domain and two frequency domain HRV features were calculated from the BBIs. The obtained results show a high level of agreement between radar-extracted and ECG-extracted HRV features. Low computation complexity makes this algorithm suitable for real-time monitoring.

High-Accuracy Real-Time Monitoring of Heart Rate Variability Using 24 GHz Continuous-Wave Doppler Radar