• J Clin Monit Comput · Aug 2018

    K-band Doppler radar for contact-less overnight sleep marker assessment: a pilot validation study.

    • Rakesh Vasireddy, Corinne Roth, Johannes Mathis, Josef Goette, Marcel Jacomet, and Andreas Vogt.
    • Department of Anaesthesiology & Pain Medicine, lnselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
    • J Clin Monit Comput. 2018 Aug 1; 32 (4): 729-740.

    AbstractAn estimated 45 million persons in Europe are annually subjected to sleep-wake disorders. State-of-the-art polysomnography provides sophisticated insights into sleep (patho)physiology. A drawback of the method, however, is the obtrusive setting dependent on a clinical-based sleep laboratory with high operational costs. A contact-less prototype was developed to monitor limb movements and vital signs during sleep. A dual channel K-band Doppler radar transceiver captured limb movements and periodic chest wall motion due to respiration and heart activity. A wavelet transform based multi-resolution analysis (MRA) approach isolated limb movements, respiration, and heart rate from the demodulated signal. A test bench setup characterized the prototype simulating near physiological chest wall motions caused by periodic respiration and heartbeats in humans. Single- and multi-tone test bench simulations showed extremely low relative percentage errors of the prototype for respiratory and heart rate within -2 and 1%. The performance of the prototype was validated in overnight comparative studies, involving two healthy volunteers, with polysomnography as the reference. The prototype has successfully classified limb movements, with a sensitivity and specificity of 88.9 and 76.8% respectively, and has achieved accurate respiratory and heart rate measurement performance with overall absolute errors of 1 breath per minute for respiration and 3 beats per minute for heart rate. This pilot study shows that K-band Doppler radar and wavelet transform MRA seem to be valid for overnight sleep marker assessment. The contact-less approach might offer a promising solution for home-based sleep monitoring and assessment.

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