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MMT-HEAR:使用红外超宽带雷达的多个移动目标心跳估计与恢复

MMT-HEAR: Multiple Moving Targets Heartbeats Estimation and Recovery Using IR-UWB Radars.

作者信息

Yang Xiuzhu, Zhang Xinyue, Qian Hongyu, Ding Yi, Zhang Lin

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:5733-5736. doi: 10.1109/EMBC44109.2020.9175318.

Abstract

Populations around the world are rapidly ageing. Age-friendly environments address the significance of continuous inhome vital sign monitoring. Impulse Radio Ultra-WideBand (IR-UWB) radar serves as a household healthcare assistance, providing non-contact vital sign monitoring without privacy issues and illumination limitation. However, the body movements bring difficulty in extracting heartbeat from radar signals, let alone obtaining complete information with body occlusions among multiple targets. This paper proposes a Multiple Moving Targets Heartbeat Estimation And Recovery (MMT-HEAR) approach to extract vital signs using IR-UWB radars. CLEAN and Joint Probability Data Association (JPDA) algorithms are firstly performed on each radar to estimate target-to-antenna distances of multiple targets. Considering signal obstruction and attenuation for targets occluded by others, the location-based distance optimization is proposed to refine these distances by combining information from all radars. Then the mapping from signal amplitudes to refined distances is introduced and combined with the Variational Nonlinear Chirp Mode Decomposition (VNCMD) to extract vital signs with body movements. To the best of our knowledge, this is the first attempt to monitor vital signs of multiple moving targets with radars. The averaging accuracy for two moving targets heartbeat monitoring during a 20-minutes observation is 85.93% with MMT-HEAR. Compared to two other conventional methods, the MMT-HEAR approach yields improvements of 16.11% and 10.16%, revealing the efficiency and robustness of this proposed approach.

摘要

全球人口正在迅速老龄化。对年龄友好的环境凸显了持续进行家庭生命体征监测的重要性。脉冲无线电超宽带(IR-UWB)雷达可作为家庭医疗保健辅助设备,提供非接触式生命体征监测,不存在隐私问题和光照限制。然而,人体运动给从雷达信号中提取心跳带来了困难,更不用说在多个目标存在身体遮挡的情况下获取完整信息了。本文提出了一种多移动目标心跳估计与恢复(MMT-HEAR)方法,用于使用IR-UWB雷达提取生命体征。首先在每个雷达上执行CLEAN和联合概率数据关联(JPDA)算法,以估计多个目标到天线的距离。考虑到被其他目标遮挡的目标的信号阻塞和衰减,提出了基于位置的距离优化方法,通过结合所有雷达的信息来细化这些距离。然后引入从信号幅度到细化距离的映射,并与变分非线性啁啾模式分解(VNCMD)相结合,以提取有身体运动时的生命体征。据我们所知,这是首次尝试用雷达监测多个移动目标的生命体征。使用MMT-HEAR在20分钟观察期间对两个移动目标心跳监测的平均准确率为85.93%。与其他两种传统方法相比,MMT-HEAR方法的准确率提高了16.11%和10.16%,显示了该方法的有效性和鲁棒性。

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