Noncontact identification of sleep-disturbed breathing from smartphone-recorded sounds validated by polysomnography

Sleep & Breathing = Schlaf & Atmung
Sanjiv NarayanRuchir Sehra

Abstract

Diagnosis of obstructive sleep apnea by the gold-standard of polysomnography (PSG), or by home sleep testing (HST), requires numerous physical connections to the patient which may restrict use of these tools for early screening. We hypothesized that normal and disturbed breathing may be detected by a consumer smartphone without physical connections to the patient using novel algorithms to analyze ambient sound. We studied 91 patients undergoing clinically indicated PSG. Phase I: In a derivation cohort (n = 32), we placed an unmodified Samsung Galaxy S5 without external microphone near the bed to record ambient sounds. We analyzed 12,352 discrete breath/non-breath sounds (386/patient), from which we developed algorithms to remove noise, and detect breaths as envelopes of spectral peaks. Phase II: In a distinct validation cohort (n = 59), we tested the ability of acoustic algorithms to detect AHI < 15 vs AHI > 15 on PSG. Smartphone-recorded sound analyses detected the presence, absence, and types of breath sound. Phase I: In the derivation cohort, spectral analysis identified breaths and apneas with a c-statistic of 0.91, and loud obstruction sounds with c-statistic of 0.95 on receiver operating characteristic analyses, relative ...Continue Reading

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Citations

Apr 21, 2020·CA: a Cancer Journal for Clinicians·Heather S L JimPeter A S Johnstone
Jun 9, 2020·Sleep & Breathing = Schlaf & Atmung·Tharun Niranjan Gomudurai PandianSanjiv Narayan
Oct 13, 2020·Advanced Materials Technologies·Siddarth ArumugamSamuel K Sia
Jan 24, 2021·Sleep & Breathing = Schlaf & Atmung·Lucia Zamora-MolinaEduardo Garcia-Pachon
Apr 13, 2021·Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine·Bochun WangDemin Han

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