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Fast and cost-effective method for non-contact respiration rate tracking using UWB impulse radar

机译:使用UWB脉冲雷达的非接触式呼吸速率跟踪快速且经济高效的方法

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摘要

Breathing rate monitoring for a long period provides a valuable indicator about human health and an early warning of possible disasters on the well-being. To gain a comfortable and adequate measurement without restricting the person's privacy, this study investigates a novel non-contact-based solution using ultra wide-band (UWB) impulse radar. We propose a fast and low-cost method for breathing events detection and respiration rate (RR) tracking. This novel approach consists of three main parts: vital signs (VS) patterns extraction based on the Generalized Goertzel Algorithm (GGA) avoiding the prior knowledge of the person's location and overcoming the effect of the clutter. RR tracking built on the complex adaptive notch filter (CANF) with a variable step size to obtain a robust estimation under the presence of sparse random body movement (SRBM) and fast tracking of the breath variability. Finally, we introduce a control chart of the breathing process using the double exponential moving average (DEMA) in order to detect the apnea events. The proposed method is evaluated using two sets of experiments, from mechanical vibrating structure to human subject. The results demonstrate that the proposed system is a promising and effective solution and provides wide usability for continuous monitoring applications. Moreover, it outperforms the state-of-the-art, in terms of computation cost and space complexity.
机译:长时间的呼吸频率监测为人类健康提供了一个有价值的指标,并对可能发生的灾难提供了早期预警。为了在不限制个人隐私的情况下获得舒适和充分的测量,本研究研究使用超宽带(UWB)脉冲雷达研究了一种新的非接触式解决方案。我们提出了一种快速、低成本的呼吸事件检测和呼吸频率(RR)跟踪方法。该方法包括三个主要部分:基于广义Goertzel算法(GGA)的生命体征(VS)模式提取,避免了人的位置先验知识,克服了杂波的影响。RR跟踪建立在可变步长的复自适应陷波滤波器(CANF)上,以在存在稀疏随机身体运动(SRBM)的情况下获得鲁棒估计,并快速跟踪呼吸变异性。最后,为了检测呼吸暂停事件,我们介绍了一个使用双指数移动平均(DEMA)的呼吸过程控制图。从机械振动结构到人体实验两组实验对所提出的方法进行了评估。结果表明,该系统是一个有前途的有效解决方案,为连续监测应用提供了广泛的可用性。此外,在计算成本和空间复杂度方面,它的性能优于最新技术。

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