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Short-Range Vital Signs Sensing Based on EEMD and CWT Using IR-UWB Radar

机译:基于IRMD和CWT的IR-UWB雷达短程生命体征传感

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摘要

The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications.
机译:所描述的雷达传感器实现了医疗保健监控,该医疗保健监控能够检测到由心肺活动引起的被检者的胸壁运动,并且无线估计被检者的呼吸和心跳率,而无需在身体上安装任何设备。传统的单音多普勒雷达只能捕获多普勒信号,因为缺乏非接触式传感器的带宽信息。相比之下,我们充分利用脉冲无线电超宽带(IR-UWB)雷达来实现低功耗和便捷的便携性,并具有灵活的检测范围和理想的精度。联合提出了一种基于改进的集成经验模态分解(EEMD)的降噪方法和一种基于连续小波变换(CWT)的生命体征分离方法,以提高信噪比(SNR)以获取准确的信号。呼吸和心跳率。实验结果表明,可以在不同条件下准确提取呼吸和心跳信号。这种非接触式医疗传感器系统证明了将紧凑型IR-UWB雷达用于新兴生物医学应用的商业可行性和可及性。

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