Support vector machines for automated snoring detection: proof-of-concept.

Journal: Sleep & breathing = Schlaf & Atmung
Published Date: Mar 1, 2017

Abstract

BACKGROUND: Snoring has been shown to be associated with adverse physical and mental health, independent of the effects of sleep disordered breathing. Despite increasing evidence for the risks of snoring, few studies on sleep and health include objective measures of snoring. One reason for this methodological limitation is the difficulty of quantifying snoring. Conventional methods may rely on manual scoring of snore events by trained human scorers, but this process is both time- and labor-intensive, making the measurement of objective snoring impractical for large or multi-night studies.

Authors

  • Laura B Samuelsson
    Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Anusha A Rangarajan
    Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Kenji Shimada
    Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Robert T Krafty
    Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
  • Daniel J Buysse
    Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
  • Patrick J Strollo
    Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
  • Howard M Kravitz
    Department of Psychiatry and Department of Preventive Medicine, Rush University, Chicago, IL, USA.
  • Huiyong Zheng
    Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Martica H Hall
    Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA. hallmh@upmc.edu.

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