Neural Network-Based Prediction of Perceived Sleep Quality Through Wearable Device Data.

Journal: Studies in health technology and informatics
PMID: 38682534

Abstract

BACKGROUND: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics from 18 participants over four weeks, including heart rate, physical activity, and both device-measured and self-reported sleep quality.

Authors

  • Martin Baumgartner
    Paediatric Neuro-Oncology Research Group, Department of Oncology, Children's Research Center, University Children's Hospital Zürich, Lengghalde 5, 8008, Zürich, Switzerland.
  • Manuel Grössl
    University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria.
  • Raphaela Haumer
    University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria.
  • Katharina Poimer
    University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria.
  • Flora Prantl
    University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria.
  • Katharina Weick
    University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria.
  • Markus Falgenhauer
    AIT Austrian Institute of Technology, Graz & Vienna, Austria.
  • Stefan Beyer
    AIT Austrian Institute of Technology, Graz & Vienna, Austria.
  • Andreas Ziegl
    AIT Austrian Institute of Technology, Graz / Vienna, Austria.
  • Aaron Lauschensky
    AIT Austrian Institute of Technology, Graz, Austria.
  • Fabian Wiesmüller
    Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria.
  • Karl Kreiner
    AIT Austrian Institute of Technology, Austria.
  • Dieter Hayn
    AIT Austrian Institute of Technology.
  • Günter Schreier
    AIT Austrian Institute of Technology, Austria.

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