Heartbeat detection using a Doppler radar sensor based on the scaling function of wavelet transform

The heartbeat detection using the scaling function of Wavelet transform is proposed for a Doppler radar sensor. The conventional methods such as the fast-Fourier transform and the autocorrelation show the respiration rate and the heartbeat from the raw data of the radar sensors acquiring for a sufficient sampling time. The methods have the limit to detect the biometric information that varies with real-time because they only show the overall statistical information of the sampled data. In the proposed method, the scaling function in the Daubechies wavelet transform can be used to accurately find out the periodicity of radar signals for detecting heartbeat varying in real-time. The results of the signal processing using the radar signals acquired for 3 min results show that the proposed method lowered a mean error rate of 2.5% and a SD of 2.0% compared with the method using the wavelet function. The proposed method in the measurement for 1 minute using the radar sensor also showed the lowest mean error rate of 3.8% and the low SD of 3.2% using the contact sensor as the reference among various signal processing methods including auto-correlation and peak detection with filtering.