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Validation of snoring detection using a smartphone app
PURPOSE: Snoring 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....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857100/ https://www.ncbi.nlm.nih.gov/pubmed/33811634 http://dx.doi.org/10.1007/s11325-021-02359-3 |
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author | Chiang, Jui-Kun Lin, Yen-Chang Lin, Chih-Wen Ting, Ching-Shiung Chiang, Yi-Ying Kao, Yee-Hsin |
author_facet | Chiang, Jui-Kun Lin, Yen-Chang Lin, Chih-Wen Ting, Ching-Shiung Chiang, Yi-Ying Kao, Yee-Hsin |
author_sort | Chiang, Jui-Kun |
collection | PubMed |
description | PURPOSE: Snoring 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. METHODS: Snoring 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. RESULTS: In 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. CONCLUSION: Snore 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. |
format | Online Article Text |
id | pubmed-8857100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-88571002022-02-23 Validation of snoring detection using a smartphone app Chiang, Jui-Kun Lin, Yen-Chang Lin, Chih-Wen Ting, Ching-Shiung Chiang, Yi-Ying Kao, Yee-Hsin Sleep Breath Sleep Breathing Physiology and Disorders • Original Article PURPOSE: Snoring 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. METHODS: Snoring 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. RESULTS: In 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. CONCLUSION: Snore 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. Springer International Publishing 2021-04-03 2022 /pmc/articles/PMC8857100/ /pubmed/33811634 http://dx.doi.org/10.1007/s11325-021-02359-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Sleep Breathing Physiology and Disorders • Original Article Chiang, Jui-Kun Lin, Yen-Chang Lin, Chih-Wen Ting, Ching-Shiung Chiang, Yi-Ying Kao, Yee-Hsin Validation of snoring detection using a smartphone app |
title | Validation of snoring detection using a smartphone app |
title_full | Validation of snoring detection using a smartphone app |
title_fullStr | Validation of snoring detection using a smartphone app |
title_full_unstemmed | Validation of snoring detection using a smartphone app |
title_short | Validation of snoring detection using a smartphone app |
title_sort | validation of snoring detection using a smartphone app |
topic | Sleep Breathing Physiology and Disorders • Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857100/ https://www.ncbi.nlm.nih.gov/pubmed/33811634 http://dx.doi.org/10.1007/s11325-021-02359-3 |
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