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Wavelet Analysis Based Noncontact Vital Signal Measurements Using mm-Wave Radar

机译:基于小波分析的基于MM波雷达的非接触式重要信号测量

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Instantaneous physiological signal rates related to cardiopulmonary activities are important indicators of human health assessment. Noncontact vital signals detection using microwave radar is preferable due to its zero disturbance to the subject. This paper presents a Wavelet Analysis (WA) based noncontact heartbeat and respiration signals detection algorithm using millimeter Frequency Modulated Continuous Wave (FMCW) radar. In WA, wavelet packet decomposition is applied to separate heartbeat and respiration signals from radar signal and continuous wavelet transform is used for time frequency analysis. Comparison experiments have been conducted with wearable devices on 10 subjects. Compared with the measurement result of the reference sensor, the average absolute error percentage is less than 2.0% and 3.5% for respiration and heart rate, respectively. In addition, the proposed method improves the accuracy of vital signals detection in comparison with Bandpass filter and Peak Detection (BPK).
机译:与心肺活动相关的瞬时生理信号率是人体健康评估的重要指标。由于其对对象的零干扰,优选使用微波雷达的非接触式重要信号检测。本文介绍了一种基于小波分析(WA)的非接触心跳和呼吸信号检测算法,使用毫米频率调制的连续波(FMCW)雷达。在WA中,将小波分组分解应用于单独的心跳和来自雷达信号的呼吸信号,连续小波变换用于时间频率分析。在10个受试者上使用可穿戴设备进行比较实验。与参考传感器的测量结果相比,呼吸和心率的平均绝对误差百分比分别小于2.0%和3.5%。此外,与带通滤波器和峰值检测(BPK)相比,所提出的方法提高了重要信号检测的准确性。

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