Respiratory Frequency Estimation Method Based on Periodic Features Using UWB Radar

In this paper, we propose an algorithm for adaptively extracting respiratory waveform and estimating respiratory rate in different target states based on ultrawideband (UWB) radar. At present, the respiratory rate can be estimated in most algorithms only when the target is stationary. The proposed algorithm performs target state determination through fast time and slow time matrices respectively. The two detection procedures are cascaded to determine the target's state (namely, target absence, motion and breathing) and the human breathing area. In the following, the proposed algorithm adaptively extracts the respiratory waveform through the features of respiratory periodicity, which can overcome the shortcoming caused by the maximum energy range bin approach in the case of low signal-noise ratio (SNR). Finally, the respiratory frequency is estimated by the frequency time phase regression (FTPR) method. The experimental results show that the mean square error (MSE) between the estimated respiratory rate and the result of the multi-channel physiological recorder is 0.4664 breath²/min.