Key result
Second-order cyclostationary model successfully extracts vital signs from modulated radar signals in single-subject experiments.
Why the study?
Unobtrusive and continuous monitoring of cardiopulmonary activity at a distance requires effective signal processing methods to extract vital signs from Doppler radar signals contaminated by noise and motion artefacts.
A second-order cyclostationary model successfully extracts vital signs from Doppler radar signals, validated in simulations and a single-subject experiment.
Provides a cyclostationary model for remote vital-signs radar; leaves open prospective clinical validation before practice adoption.
Unobtrusive and continuous monitoring of cardiopulmonary activity at a distance provides a potential tool in making health care and emergency delivery more efficient. Doppler radar remote sensing of vital signs has shown promise to this end, with proof of concept demonstrated for various applications such as more comfortable monitoring for many people. In this study, the authors present a second‐order cyclostationary model for the returned amplitude and frequency modulated radar signal, which is contaminated with various noises, body motion artefacts and dc offset, to extract vital signs. They validate their model with confidence interval extraction from 500 simulation runs and also with 50 experiment runs on a female student using a miniaturised non‐contact heartbeat and respiration monitoring radar system based on the quadrature Doppler effect.
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Kazemi et al. (2015) studied Cardiopulmonary activity monitoring (n=1). Second-order cyclostationary model for Doppler radar signal processing was evaluated on Extraction of vital signs (heartbeat and respiration). A second-order cyclostationary model successfully extracted vital signs from amplitude and frequency modulated radar signals in 500 simulation runs and 50 experimental runs on a single subject.
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