用于超宽带（UWB）雷达非接触生命体征监测的频谱平均谐波路径（SHAPA）算法。

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

作者信息

Javaid Abdul Q, Weitnauer Mary Ann

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2241-4. doi: 10.1109/EMBC.2014.6944065.

DOI:10.1109/EMBC.2014.6944065

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.

摘要

我们介绍了用于通过脉冲无线电超宽带（IR-UWB）雷达估计心率（HR）和呼吸率（RR）的频谱平均谐波路径（SHAPA）算法。呼吸和心跳引起的人体躯干的周期性运动在呼吸率和心率处诱发基频及其谐波。IR-UWB能够捕获这些频谱成分，并且频域处理能够实现低成本实现。如果基频被干扰扭曲或抵消，大多数现有的在频域或时域中识别基频成分以估计HR和/或RR的方法会导致显著误差。SHAPA算法（1）利用干扰较少的HR谐波，并且（2）利用先前频谱中的信息来更可靠、更稳健地估计所考虑频谱中的基频。HR估计的示例实验结果表明了我们的算法如何消除由干扰引起的误差，并产生多16%至60%的有效估计。