ArticleSleep & breathing = Schlaf & Atmung2022
Validation of snoring detection using a smartphone app.
Article in Sleep & breathing = Schlaf & Atmung, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Health Sciences Students' Knowledge and Attitudes Toward Snoring: A Cross-Sectional Study in Jeddah, Saudi Arabia.Nature and science of sleep · 2026Article
- Impacts of an Oral Appliance on Snoring in Adults with Varying Degrees of Snoring Severity: A Preliminary Study.Medicina (Kaunas, Lithuania) · 2025Article
- Accuracy of Smartphone-Mediated Snore Detection in a Simulated Real-World Setting: Algorithm Development and Validation.JMIR formative research · 2025Article
- Real-Time Snoring Detection Using Deep Learning: A Home-Based Smartphone Approach for Sleep Monitoring.Nature and science of sleep · 2025Article
- Mobile Technologies for Monitoring Sleep Time: A Systematic Search of App Stores in Brazil.Sleep science (Sao Paulo, Brazil) · 2024Article
- Validation of Downloadable Mobile Snore Applications by Polysomnography (PSG).Nature and science of sleep · 2024Article
- High-Speed Network DDoS Attack Detection: A Survey.Sensors (Basel, Switzerland) · 2023Review
- Long-term benefits of a new oral appliance on adult snoring: a trend analysis.Multidisciplinary respiratory medicine · 2022Article
- Effects of a novel oral appliance on snoring in adults: A pilot study.Journal of dental sciences · 2022Article
- Accuracy of a Smartphone Application Measuring Snoring in Adults-How Smart Is It Actually?International journal of environmental research and public health · 2021Article
- Effect of myofunctional therapy on snoring in obese patients: a randomized trial.Sleep science (Sao Paulo, Brazil)Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSnoring is closely related to obstructive sleep apnea in adults. The increasing abundance and availability of smartphone technology has facilitated the examination and monitoring of snoring at home through snoring apps. However, the accuracy of snoring detection by snoring apps is unclear. This study explored the snoring detection accuracy of Snore Clock-a paid snoring detection app for smartphones.
methodsSnoring rates were detected by smartphones that had been installed with the paid app Snore Clock. The app provides information on the following variables: sleep duration, snoring duration, snoring loudness (in dB), maximum snoring loudness (in dB), and snoring duration rate (%). In brief, we first reviewed the snoring rates detected by Snore Clock; thereafter, an ear, nose, and throat specialist reviewed the actual snoring rates by using the playback of the app recordings.
resultsIn total, the 201 snoring records of 11 patients were analyzed. Snoring rates measured by Snore Clock and those measured manually were closely correlated (r = 0.907). The mean snoring detection accuracy rate of Snore Clock was 95%, with a positive predictive value, negative predictive value, sensitivity, and specificity of 65% ± 35%, 97% ± 4%, 78% ± 25%, and 97% ± 4%, respectively. However, the higher the snoring rates, the higher were the false-negative rates for the app.
conclusionSnore Clock is compatible with various brands of smartphones and has a high predictive value for snoring. Based on the strong correlation between Snore Clock and manual approaches for snoring detection, these findings have validated that Snore Clock has the capacity for at-home snoring detection.
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