TY - JOUR
T1 - High-Accuracy Heart Rate Variability Monitoring Using Doppler Radar Based on Gaussian Pulse Train Modeling and FTPR Algorithm
AU - Nosrati, Mehrdad
AU - Tavassolian, Negar
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/1
Y1 - 2018/1
N2 - This paper presents the theoretical and experimental study of a novel noncontact heart-beat signal modeling and estimation algorithm using a compact 2.4-GHz Doppler radar. The proposed technique is able to accurately reconstruct the heart-beat signal and generates heart rate variability indices at a distance of 1.5 m away from the human body. The feasibility of the proposed approach is validated by obtaining data from eight human subjects and comparing them with photoplethysmography (PPG) measurements. A Gaussian pulse train model is suggested for the heart-beat signal along with a modified-and-combined autocorrelation and frequency-time phase regression technique for high-accuracy detection of the human heart-beat rate. The proposed method is accurate, robust, and simple, and demonstrates an average heart-beat detection accuracy of more than 90% at a distance of 1.5 m away from the subjects. In addition, the average beat-to-beat time intervals extracted from the proposed model and signal reconstruction method show less than 2% error compared to PPG measurements. Bland-Altman analysis further validated the accuracy of the proposed approach in comparison with reference data.
AB - This paper presents the theoretical and experimental study of a novel noncontact heart-beat signal modeling and estimation algorithm using a compact 2.4-GHz Doppler radar. The proposed technique is able to accurately reconstruct the heart-beat signal and generates heart rate variability indices at a distance of 1.5 m away from the human body. The feasibility of the proposed approach is validated by obtaining data from eight human subjects and comparing them with photoplethysmography (PPG) measurements. A Gaussian pulse train model is suggested for the heart-beat signal along with a modified-and-combined autocorrelation and frequency-time phase regression technique for high-accuracy detection of the human heart-beat rate. The proposed method is accurate, robust, and simple, and demonstrates an average heart-beat detection accuracy of more than 90% at a distance of 1.5 m away from the subjects. In addition, the average beat-to-beat time intervals extracted from the proposed model and signal reconstruction method show less than 2% error compared to PPG measurements. Bland-Altman analysis further validated the accuracy of the proposed approach in comparison with reference data.
KW - Doppler radar
KW - frequency-time phase regression (FTPR) technique
KW - heart rate monitoring
KW - heart rate variability (HRV) analysis
KW - noncontact monitoring
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U2 - 10.1109/TMTT.2017.2721407
DO - 10.1109/TMTT.2017.2721407
M3 - Article
AN - SCOPUS:85028829738
SN - 0018-9480
VL - 66
SP - 556
EP - 567
JO - IEEE Transactions on Microwave Theory and Techniques
JF - IEEE Transactions on Microwave Theory and Techniques
IS - 1
M1 - 7986995
ER -