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. 2022 Mar;26(1):81-87.
doi: 10.1007/s11325-021-02359-3. Epub 2021 Apr 3.

Validation of snoring detection using a smartphone app

Jui-Kun Chiang  1 , Yen-Chang Lin  2 , Chih-Wen Lin  3   4 , Ching-Shiung Ting  5 , Yi-Ying Chiang  2 , Yee-Hsin Kao  6
Affiliations

Validation of snoring detection using a smartphone app

Jui-Kun Chiang et al. Sleep Breath. 2022 Mar.

Abstract

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.

Keywords: App; Smartphones; Snore Clock; Snoring.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Scatter plot of snoring rates determined by Snore Clock and a manual method of measurement
Fig. 2
Fig. 2
Scatter plot of the false-negative snoring rates by Snore Clock vs. the rates by Snore Clock
Fig. 3
Fig. 3
Scatter plots of sensitivities versus 1 – specificities and the smoothing line
See this image and copyright information in PMC

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