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Fast heart rate extraction using CW Doppler radar with interpolated discrete Fourier transform algorithm

机译:具有内插离散傅里叶变换算法的CW多普勒雷达快速心率提取

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Doppler radar-based fast heart rate (HR) extraction has great application potential in stress and emotion recognition, anxiety treatments, etc. However, fast extraction of HR is still a great challenge for the vital sign detection applying the traditional discrete Fourier transform (DFT) method based on a continuous-wave (CW) Doppler radar sensor. When applying traditional DFT to the baseband signal analysis, the spectrum resolution will become insufficient if the time window is less than 10 s. In this paper, an interpolated DFT algorithm based on a poly-item cosine window is introduced to achieve fast extraction of HR with only 3 s data length. In addition, the leakage and grid effect phenomenon is presented to show the defects caused by the traditional DFT method. To verify the effectiveness of the proposed method, simulations are performed and experiments are executed using a 10-GHz CW Doppler radar sensor platform. Compared with the traditional DFT method, the interpolated DFT method reduces the average HR error from 8.48% to 1.87% based on the Hanning window and from 8.48% to 1.45% based on the rectangular window.
机译:基于多普勒雷达的快速心率(HR)提取具有强调和情感识别,焦虑治疗等的应用潜力。然而,人力资源的快速提取仍然是应用传统离散傅立叶变换的重要标志检测的巨大挑战(DFT )基于连续波(CW)多普勒雷达传感器的方法。将传统DFT应用于基带信号分析时,如果时间窗口小于10秒,频谱分辨率将变得不足。在本文中,引入了基于多项余弦窗口的内插DFT算法,以实现仅具有3个数据长度的HR的快速提取。此外,提出了泄漏和电网效应现象以显示传统DFT方法引起的缺陷。为了验证所提出的方法的有效性,执行模拟,使用10-GHz CW多普勒雷达传感器平台执行实验。与传统的DFT方法相比,内插DFT方法基于汉宁窗口将平均HR误差从8.48%降至1.87%,并基于矩形窗口的8.48%至1.45%。

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