Low-complexity Wireless Monitoring of Respiratory Movements Using Ultra-wideband Impulse Response Estimation
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AbstractIn this paper; we present a comprehensive scheme for wireless monitoring of the respiratory movements in humans. Our scheme overcomes the challenges low signal-to-noise ratio, background clutter and high sampling rates. It is based on the estimation of the ultra-wideband channel impulse response. We suggest techniques for dealing with background clutter in situations when it might be time variant. We also present a novel methodology for reducing the required sampling rate of the system significantly while achieving the accuracy offered by the Nyquist rate. Performance results from simulations conducted with pre-recorded respiratory signals demonstrate the robustness of our scheme for tackling the above challenges and providing a low-complexity solution for the monitoring of respiratory movements.
CitationLow-complexity Wireless Monitoring of Respiratory Movements Using Ultra-wideband Impulse Response Estimation