Human respiration rate estimation using ultra-wideband distributed cognitive radar system |
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Authors: | Yifan Chen Predrag Rapajic |
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Affiliation: | School of Engineering, University of Greenwich, Kent ME4 4TB, UK ;School of Computer, Electronic and Information, Guangxi University, Nanning 530004, PRC School of Engineering, University of Greenwich, Kent ME4 4TB, UK |
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Abstract: | It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems,which shows promise in home healthcare, rescue, and security applications. In this paper, we first present a multi-ray propagation model for UWB signal, which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces. A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently,a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs. We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture. |
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Keywords: | Medical and patient monitoring sensing technologies and signal processing vital sign ultra-wideband distributed cognitive radar respiration rate estimation. |
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