Why the study?
Monitoring HRV using continuous wave Doppler radar requires shortening the time window to less than 5 s, causing spectrum leakage and degrading measurement accuracy.
Does the Quinn frequency interpolation algorithm improve HRV extraction accuracy using CW Doppler radar compared to other algorithms?
Does the Quinn frequency interpolation algorithm improve HRV extraction accuracy using CW Doppler radar compared to other algorithms?
The Quinn frequency interpolation algorithm enables accurate non-contact HRV monitoring using CW Doppler radar with an average error of 3.61%.
Answers are grounded in this paper and cite their sources.
Short-window CW Doppler radar enables real-time HRV extraction; leaves open clinical validation before cardiovascular monitoring use.
Real-time monitoring of heart rate (HR), i.e., extraction of heart rate variability (HRV), plays an important role in diagnosis and prevention of cardiovascular diseases. Compared with traditional contact monitoring devices, the use of continuous wave (CW) Doppler radar to monitor HRV does not require contact and is not sensitive to light and temperature, which makes it more and more popular. To monitor the HRV based on CW Doppler radar, the time window must be shortened to less than 5 s, which will lead to the spectrum leakage and degrade the measurement accuracy of HRV. To solve this problem, a custom CW Doppler radar has been developed in an integrated fashion on a single PCB, whose transmitting frequency and power of the radar are 24 GHz and 3 dBm, respectively. Furthermore, four frequency interpolation algorithms are introduced to compare their extraction accuracy. Experiments are performed on three subjects, and results show that the Quinn algorithm can obtain best HRV extraction results compared with other algorithms. Specially, the average HRV extraction error is 3.61% using the Quinn algorithm.
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Shi et al. (2023) studied this question.
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