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Related Concept Videos

Sleep Apnea01:21

Sleep Apnea

283
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.
The condition is more prevalent among...
283

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Validation of snoring detection using a smartphone app.

Jui-Kun Chiang1, Yen-Chang Lin2, Chih-Wen Lin3,4

  • 1Department of Family Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, 2, Minsheng Road, Dalin, 62247, Chiayi, Taiwan.

Sleep & Breathing = Schlaf & Atmung
|April 3, 2021
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Summary

Snoring detection apps like Snore Clock show high accuracy for at-home monitoring. This study validated the app

Keywords:
AppSmartphonesSnore ClockSnoring

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Area of Science:

  • Sleep Science
  • Digital Health Technology

Background:

  • Snoring is a common symptom linked to obstructive sleep apnea in adults.
  • Smartphone technology enables convenient at-home snoring monitoring via dedicated apps.
  • The diagnostic accuracy of these snoring detection applications remains largely unverified.

Purpose of the Study:

  • To evaluate the snoring detection accuracy of Snore Clock, a commercially available smartphone application.
  • To compare the app's performance against manual snoring rate assessments by a specialist.

Main Methods:

  • Snoring data were collected using the Snore Clock app on smartphones.
  • The app recorded sleep duration, snoring duration, loudness (dB), and snoring rate (%).
  • An ENT specialist manually reviewed and validated the app's snoring detection results.

Main Results:

  • Analysis of 201 snoring records from 11 patients showed a strong correlation (r=0.907) between app and manual detection.
  • Snore Clock demonstrated a mean snoring detection accuracy of 95%.
  • Positive predictive value was 65%±35%, negative predictive value 97%±4%, sensitivity 78%±25%, and specificity 97%±4%.

Conclusions:

  • Snore Clock exhibits high compatibility across smartphone brands and strong predictive capabilities for snoring.
  • The app's validated accuracy supports its utility for convenient at-home snoring detection.
  • Findings suggest Snore Clock can be a reliable tool for initial snoring assessment.