首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Spectrum-averaged Harmonic Path (SHAPA) algorithm for non-contact vital sign monitoring with ultra-wideband (UWB) radar
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Spectrum-averaged Harmonic Path (SHAPA) algorithm for non-contact vital sign monitoring with ultra-wideband (UWB) radar

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

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摘要

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.
机译:我们介绍了频谱平均谐波路径(SHAPA)算法,用于通过脉冲无线电超宽带(IR-UWB)雷达估算心率(HR)和呼吸频率(RR)。由呼吸和心跳引起的人体躯干的周期性运动会在呼吸和心率上诱发基本频率及其谐波。 IR-UWB可以捕获这些频谱分量,而频域处理则可以实现低成本实施。如果基频因干扰而失真或抵消,则大多数现有的在频域或时域中识别基频分量以估算HR和/或RR的方法都会导致明显的误差。 SHAPA算法(1)利用了干扰较少的HR谐波,并且(2)利用先前频谱中的信息来实现对所考虑频谱中基频的更可靠和更可靠的估计。 HR估算的示例实验结果证明了我们的算法如何消除由干扰引起的错误,并产生了16%至60%的有效估算值。

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