An improved real-time detection algorithm based on frequency interpolation

Abstract

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.

Innovative non-contact r-r intervals estimation using viterbi algorithm with Squared Branch Metric (VSBM)

“…Notably, the variation in R-R Interval (RRI) has been identified as a valuable parameter for assessing both cardiovascular and non-cardiovascular conditions in a subject (Aram & Setarehdan, 2013;W. Hu et al, 2014;Kitagawa et al, 2022;Shi et al, 2023;Xiang et al, 2023;Yamamoto & Ohtsuki, 2021;Ye & Ohtsuki, 2021;Zar & Tun, 2022). Traditional approaches for RRI estimation involve the use of established heartbeat monitoring systems such as Electrocardiogram (ECG) or Photoplethysmography (PPG) (Tun, 2021).…”