Quadrature Cosine Transform (QCT) With Varying Window Length (VWL) Technique for Noncontact Vital Sign Monitoring Using a Continuous-Wave (CW) Radar

For noncontact vital sign monitoring by using a continuous-wave (CW) radar, the quadrature cosine transform (QCT) with varying window length (VWL) technique is proposed in this article for the first time. The novel algorithm can directly yield the vibration frequency of the radar's output IQ si...

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Bibliographic Details
Published in:IEEE transactions on microwave theory and techniques 2022-03, Vol.70 (3), p.1639-1650
Main Authors: Shih, Ju-Yin, Wang, Fu-Kang
Format: Article
Language:English
Subjects:
Algorithms
Calibration
Computed tomography
Continuous radiation
Continuous-wave (CW) radar
demodulation
Fourier transforms
Harmonic analysis
Heart rate
Heart rate variability
heart rate variability (HRV) trend
Intermodulation
Monitoring
quadrature cosine transform (QCT)
Quadratures
Radar
Respiratory rate
respiratory rate variability (RRV)
short-time heart rate (HR)
Signal resolution
Telemedicine
varying window length (VWL)
vital signs
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Summary:For noncontact vital sign monitoring by using a continuous-wave (CW) radar, the quadrature cosine transform (QCT) with varying window length (VWL) technique is proposed in this article for the first time. The novel algorithm can directly yield the vibration frequency of the radar's output IQ signals with multiple advantages, including the elimination of dc offset calibration and mitigation of nonlinear interferences caused by harmonic and intermodulation terms, and there is a 50% reduction in frequency resolution of the conventional Fourier transform (FT) that is commonly utilized in existing articles. Thus, it can strike a balance between accuracy and computational efficiency with a short window length. The excellent performance was demonstrated by both theoretical predictions and simulation results. Experiments involving a participant seated 1 m away from the 2.4-GHz ISM band radar prototype demonstrated that the proposed algorithm measures the respiratory rate variability (RRV) and short-time heart rate (HR) with respective errors of less than 1% and 3%. Moreover, the proposed algorithm was more accurate than conventional methods with various window lengths (3-27 s) in 10-min noncontact experiments to monitor the vital signs of ten participants.
ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2021.3135304