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Optical wrist-worn device for sleep monitoring

  • Philippe Renevey
  • Ricard Delgado-Gonzalo
  • Alia Lemkaddem
  • Martin Proença
  • Mathieu Lemay
  • Josep Solà
  • Adrian Tarniceriu
  • Mattia Bertschi
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 65)

Abstract

This paper presents and clinically validates a new method to accurately classify sleep phases within a wrist-worn device (e.g., smartwatch, fitnessband). The method combines inertial and optical sensors to compute the wearer’s motion, breathing rate, and pulse rate variability, and to estimate the different sleep stages (WAKE, REM and NREM). The presented method achieves a sensitivity and specificity for the REM of \(89.2\,\%\) and \(77.9\,\%\) respectively; for the NREM class \(83.4\,\%\) and \(84.9\,\%\) respectively; and a median accuracy of \(81.4\,\%\). The assessment of the performance was obtained by comparing to the gold standard measure in sleep monitoring, polysomnography.

Keywords

Sleep analysis pulse-rate variability photoplethysmography wearable device REM NREM classification 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Philippe Renevey
    • 1
  • Ricard Delgado-Gonzalo
    • 1
  • Alia Lemkaddem
    • 1
  • Martin Proença
    • 1
  • Mathieu Lemay
    • 1
  • Josep Solà
    • 1
  • Adrian Tarniceriu
    • 2
  • Mattia Bertschi
    • 1
  1. 1.Centre Suisse d’Électronique et de MicrotechniqueNeuchâtelSwitzerland
  2. 2.PulseON SwitzerlandNeuchâtelSwitzerland

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