Yifan Chen and Predrag Rapajic. Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System. International Journal of Automation and Computing, vol. 5, no. 4, pp. 325-333, 2008. DOI: 10.1007/s11633-008-0325-3
Citation: Yifan Chen and Predrag Rapajic. Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System. International Journal of Automation and Computing, vol. 5, no. 4, pp. 325-333, 2008. DOI: 10.1007/s11633-008-0325-3

Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System

  • 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 rheasurement 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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