Sound Recording and Acoustic Analysis of Sleep Disordered Breathing
Research type
Research Study
Full title
All-night sound recording via smartphone of subjects during multi-channel home sleep apnoea testing to generate data for the development of algorithms capable of classifying sleep disordered breathing from phone audio data alone.
IRAS ID
254185
Contact name
Guy J Brown
Contact email
Sponsor organisation
Passion For Life Healthcare (UK) Ltd
Clinicaltrials.gov Identifier
40155, CPMS ID
Duration of Study in the UK
0 years, 2 months, 30 days
Research summary
Having previously developed algorithms capable of detecting and classifying snoring from a phone app, the University of Sheffield would like to develop algorithms similarly capable of making classification assessments of obstructive sleep apnoea (OSA). The aim of this study is to record examples of OSA breathing using smartphones in a home setting while the patient simultaneously completes their routine OSA diagnostic process (home sleep apnoea test, HSAT). The Analysis Team, comprised of specified personnel from both University of Sheffield and PFL Healthcare will analyse the audio recordings by comparing them with the 'ground truth' HST data and then use machine learning techniques to develop algorithms capable of making quasi-diagnostic or screening assessments from audio signals alone.
REC name
London - Chelsea Research Ethics Committee
REC reference
18/LO/2243
Date of REC Opinion
3 Jan 2019
REC opinion
Favourable Opinion