Spectrum-averaged Harmonic Path (SHAPA) algorithm for non-contact vital sign monitoring with ultra-wideband (UWB) radar

Abstract

We introduce the Spectrum-averaged Harmonic Path (SHAPA) algorithm for estimation of heart rate (HR) and respiration rate (RR) with Impulse Radio Ultrawideband (IR-UWB) radar. Periodic movement of human torso caused by respiration and heart beat induces fundamental frequencies and their harmonics at the respiration and heart rates. IR-UWB enables capture of these spectral components and frequency domain processing enables a low cost implementation. Most existing methods of identifying the fundamental component either in frequency or time domain to estimate the HR and/or RR lead to significant error if the fundamental is distorted or cancelled by interference. The SHAPA algorithm (1) takes advantage of the HR harmonics, where there is less interference, and (2) exploits the information in previous spectra to achieve more reliable and robust estimation of the fundamental frequency in the spectrum under consideration. Example experimental results for HR estimation demonstrate how our algorithm eliminates errors caused by interference and produces 16% to 60% more valid estimates.

Detection of Heart Rate through a Wall Using UWB Impulse Radar

“…Because comparable studies utilizing UWB impulse radar to measure human heart rate through a wall did not quantify the accuracy of their heart rates, it is difficult to compare the results obtained in this paper directly with those of the other studies. However, some studies using UWB impulse radar to extract a heartbeat without wall penetration [ 16 , 17 ] found a minimum error rate of 4.0–5.4%, and even in comparison to these studies, the experimental result of this study demonstrated higher accuracy. The researchers of all comparable studies extracted heart rate in the frequency domain.…”

An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver

“…They have proposed a method that uses the feature time index with the first valley peak of the energy function of intrinsic mode functions (FVPIEF) calculated by a pseudo bi-dimension ensemble empirical mode decomposition method, which extracts the vital signals by the ensemble empirical mode decomposition (EEMD). In the References [70,71], the authors proposed Harmonic Path and Averaged Harmonic Path algorithms to accurately estimate the vital signs in the presence of breathing harmonics. In another study in Reference [72], a novel noncontract vital sign detection method based on multiple higher order cumulant is presented.…”

Estimation of Human Body Vital Signs Based on 60 GHz Doppler Radar Using a Bound-Constrained Optimization Algorithm

“…In all cases, a direct peak detection of the spectrum of reflected baseband signal is consequently not reliable any more; this requires a spectral estimation algorithm for a robust determination of the frequency components. In [ 22 , 23 ], a harmonic-path algorithm was developed to determine both heartbeat and respiration rates by taking into account all harmonic components of the whole spectrum, but the ambiguity problem is not addressed. A RELAX algorithm was used in [ 24 ] for the spectrum estimation with a 20 GHz Doppler radar, which is based on the minimization of a nonlinear least-square fitting problem.…”