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High Accuracy Heartbeat Detection from CW-Doppler Radar Using Singular Value Decomposition and Matched Filter

机译:使用奇异值分解和匹配过滤器的CW-Doppler雷达高精度心跳检测

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摘要

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.
机译:使用连续波多普勒雷达传感器(CW-DRS)的心率测量已应用于需要非接触检测的情况,例如在家庭医疗保健中监测生命体征。然而,由于CW-DRS测量胸表面的运动速度,这包括通过身体运动的心脏和呼吸信号,从叠加信号中提取心脏信息是困难的。因此,从叠加信号提取心脏信息是挑战性的。这里,我们提出了一种基于匹配滤波器的新方法来解决这个问题。该方法包括两个过程:通过由测量信号形成的轨迹矩阵的奇异值分解的自适应生成模板,并通过产生的模板和测量信号的卷积重构。使用在两个不同的实验中获得的数据集进行验证该方法,即涉及仰卧和坐姿的主体姿势的实验。心跳间隔的绝对误差和带参考的心跳间隔的偏差为1.93±1.76bpm和57.0±28.1s,用于姿势9.72±7.86bpm和81.3±24.3s,适用于姿势。

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