Abstract
Doppler radar-based fast heart rate (HR) extraction has great application potential in stress and emotion recognition, anxiety treatments, etc. However, fast extraction of HR is still a great challenge for the vital sign detection applying the traditional discrete Fourier transform (DFT) method based on a continuous-wave (CW) Doppler radar sensor. When applying traditional DFT to the baseband signal analysis, the spectrum resolution will become insufficient if the time window is less than 10 s. In this paper, an interpolated DFT algorithm based on a poly-item cosine window is introduced to achieve fast extraction of HR with only 3 s data length. In addition, the leakage and grid effect phenomenon is presented to show the defects caused by the traditional DFT method. To verify the effectiveness of the proposed method, simulations are performed and experiments are executed using a 10-GHz CW Doppler radar sensor platform. Compared with the traditional DFT method, the interpolated DFT method reduces the average HR error from 8.48% to 1.87% based on the Hanning window and from 8.48% to 1.45% based on the rectangular window.
Highlights
The first problem is that the frequency of the peak point obtained by the traditional discrete Fourier transform (DFT) method is quite different from the reference frequency
Due to the insufficient spectrum resolution caused by the short time window, the peak point obtained by the traditional DFT method is not consistent with the reference frequency point
Because of the same reason, the reference frequency point appears between the peak point and the second peak point obtained by the traditional DFT method in spectrograms, no matter the second peak point is on the right or the left of the peak point
Summary
Vital sign detection is a relevant factor in medical applications and day-to-day activities. Continuous-wave (CW) Doppler radar sensors have been widely researched for vital sign (heartbeat and respiration) detection during the last decades. Compared with the contact sensors, such as electrocardiogram (ECG) and photoplethysmogram (PPG), the CW Doppler radar sensors, with the noncontact and noninvasive characteristics, have more advantages in measurements because they do not require touching the subject’s skin or taking off the subject’s clothes.. The fast extraction of HR in near real time is required in numerous applications, such as stress and emotion recognition, anxiety treatments, etc. When using the traditional discrete Fourier transform (DFT) method, which is the most common method in measuring HR, the 5 s time window length is too short to have sufficient spectrum resolution.. To assure the detection accuracy of HR, the traditional DFT method needs a time window length T longer than. A polyphase-based discrete cosine transform method is presented in Ref. 15 for the fast extraction of HR. To achieve the fast HR extraction with high detection accuracy, the interpolated DFT algorithm is introduced based on the characteristic of the poly-item cosine window. Simulation and experimental results based on the interpolated DFT method are compared with the traditional DFT method, respectively
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