The technology of vital signs detection for the heart rate measurement using a Doppler radar system has been proven of great use, whereas it is still limited by several challenges. The major challenges are respiratory harmonic interference and random body movement (RBM), which significantly degrade the accuracy of measurement. In this paper, a novel vital signs detection method is proposed to acquire accurate heart rate measurement by jointly exploiting the respiratory harmonic cancellation method and regional hidden Markov model (RHMM) technique. The complex signal demodulation technique is firstly used to acquire an accurate respiratory rate estimation, and the respiration harmonic cancellation method is then introduced to address the harmonic interference. Finally, the RHMM technique is utilized to acquire robust and enhanced heart rate measurement by exploiting the underlying slowly-varying characteristics of the heartbeat signal to mitigate the effects of RBM. Experimental results based on a 24 GHz Doppler radar system show that the proposed method has a better performance than previous methods, whose average accuracy of the heart rate measurement reaches up to 94.5% in the RBM environment.
Instantaneous frequency (IF) estimation of multicomponent signals with time frequency (TF) overlapped components is a challenging task in radar, sonar and other applications. Viterbi algorithm (VA) on TF distribution can be potentially applied to estimate IFs of multicomponent signals, but it may track wrong IFs when signal components intersect each other in the TF domain. In order to suppress this switch problem in the original VA, this paper assumes the linearity of IFs in the overlapped regions remains unchanged, then, a novel penalty function in the modified VA based on linear least square fitting technique using adjacent several TF points is developed. Performance of the proposed algorithm on several artificial multicomponent FM signals indicates the proposed algorithm can obtain more accurate IFs by suppressing the switch problem.
Vital sign detection using Doppler radar has potential applications in the home and medical healthcare, etc. In this paper, a generalized Warblet transform (GWT) based algorithm is used to reveal the instantaneous frequency (IF) ridge of cardiopulmonary signals from the 24GHz Doppler radar. To improve the accuracy of the estimated IF in GWT, Viterbi algorithm (VA) instead of maximum method is firstly adopted in the iterative process and IF estimation, then, spectrum of IF is calculated to obtain respiration and heartbeat rates. Validation of the proposed algorithm on several simulated signals are conducted. The results show that compared with the original GWT and short time Fourier transform (STFT) combined with maximum method, the proposed algorithm can obtain more accurate IFs especially in a high noise environment.
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