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Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
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Articles linked to this work by shared authors, journal, and citation graph.

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Stated patient preferences for overnight at-home diagnostic assessment of sleep disorders.

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Patient-reported experience with hypoglossal nerve stimulation in the treatment of obstructive sleep apnea.

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Diagnosis and treatment of isolated snoring-open questions and areas for future research.

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[Acoustic information in snoring noises].

C Janott1, B Schuller2, C Heiser3

  • 1Zentralinstitut für Medizintechnik (IMETUM), Technische Universität München, Boltzmannstraße 11, 85748, Garching, Deutschland. c.janott@gmx.net.

HNO
|January 22, 2017
PubMed
Summary
This summary is machine-generated.

Acoustic analysis of snoring shows promise for diagnosing obstructive sleep apnea (OSA) severity and detecting breathing events during sleep. This non-invasive method could supplement current sleep diagnostics.

Keywords:
Machine LearningObstructive sleep apneaRespiration disordersRespiratory soundsSnoring

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Area of Science:

  • Sleep Medicine
  • Biomedical Acoustics
  • Data Analysis

Background:

  • Snoring affects over one-third of the population and is frequently linked to obstructive sleep apnea (OSA).
  • Snoring can significantly disrupt the sleep of bed partners.

Purpose of the Study:

  • To review the history and current research on acoustic analysis of snoring.
  • To explore applications in OSA severity classification, obstructive event detection, annoyance measurement, and sound source localization.

Main Methods:

  • Literature searches were conducted in PubMed and IEEE Xplore databases.
  • Publications were selected based on their relevance to the study's objectives in their titles and abstracts.

Main Results:

  • A total of 48 publications were reviewed.
  • A common limitation identified across studies is the small sample size of participants.

Conclusions:

  • Acoustic analysis of snoring presents promising results for sleep diagnostics.
  • This technique has the potential to complement established diagnostic methods for sleep disorders.