Abstract
The noncontact measurement of vital signs using ultra-wideband radar has been attracting increasing attention because it can unobtrusively provide information about the physical and mental condition of people. In particular, the continuous measurement of a person's time-varying instantaneous heart rate can estimate the activity level of the autonomic nervous system without the person wearing any sensors. Continuous heart rate measurement using radar is, however, a difficult task because accuracy is compromised by numerous factors, such as the posture and motion of the target person. In this study, we introduce techniques for increasing the accuracy and reliability of the noncontact measurement of heart rate variability. We demonstrate the performance of the proposed techniques by applying them to radar measurement data from a sleeping person, and we also compare its accuracy with electrocardiogram data.
Highlights
INTRODUCTIONHE importance of heart rate variability (HRV) has been widely recognized in healthcare and medical applications
HE importance of heart rate variability (HRV) has been widely recognized in healthcare and medical applications.Pagani et al [1] and Malliani et al [2] conducted pioneering studies in this field, and suggested the use of the low-frequency (LF)/high-frequency (HF) ratio of HRV, which is the power ratio of the LF (0.04–0.15 Hz) to the HF (0.15–0.4 Hz) components of the HRV time series, as a convenient marker for sympathetic and vagal activity balance
We introduce two techniques to improve accuracy in the measurement of the LF/HF ratio using an ultra-wideband (UWB) millimeter-wave (MMW) multipleinput multiple-output (MIMO) array radar system
Summary
HE importance of heart rate variability (HRV) has been widely recognized in healthcare and medical applications. LF and HF scatter diagrams were proposed instead of the LF/HF ratio for discriminating various nerve activity balances Based on these careful studies, HRV has been increasingly used in a wide range of applications [16]–[18]. Li and Lin [23] proposed a method to estimate heart rate based on the wavelet transform and achieved an error of 3.5% These radar-based noncontact measurement techniques have been applied to sleep monitoring [24]–[28]. By integrating these techniques, the LF/HF ratio of a sleeping person is successfully measured in a noncontact manner using a radar system.
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