Classification of respiratory effort and disordered breathing during sleep from audio and pulse oximetry signals

Brian R. Snider; Alexander Kain

doi:10.1109/ICASSP.2016.7471784

Classification of respiratory effort and disordered breathing during sleep from audio and pulse oximetry signals

Brian R. Snider, Alexander Kain

Institute on Development & Disability

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Sleep-disordered breathing (SDB) is a highly prevalent condition associated with many adverse health problems. As the current means of diagnosis (polysomnography) is obtrusive and ill-suited for mass screening of the population, we explore a minimal-contact, automatic approach that uses acoustics-based methods in conjunction with pulse oximetry. We present a two-stage method for automatically classifying breathing sounds produced during sleep to track respiratory effort and predicting disordered breathing events using respiratory effort durations and oxygen desaturations. We compare our method for tracking respiratory effort and predicting disordered breathing with human expert event scoring. Our subject-independent method tracks respiratory effort with 87% accuracy and predicts disordered breathing events with 40-52% accuracy.

Original language	English (US)
Title of host publication	2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	794-798
Number of pages	5
Volume	2016-May
ISBN (Electronic)	9781479999880
DOIs	https://doi.org/10.1109/ICASSP.2016.7471784
State	Published - May 18 2016
Event	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: Mar 20 2016 → Mar 25 2016

Other

Other	41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
Country	China
City	Shanghai
Period	3/20/16 → 3/25/16

Keywords

breathing
polysomnography
sleep apnea

ASJC Scopus subject areas

Signal Processing
Software
Electrical and Electronic Engineering

Access to Document

10.1109/ICASSP.2016.7471784

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Cite this

Snider, B. R., & Kain, A. (2016). Classification of respiratory effort and disordered breathing during sleep from audio and pulse oximetry signals. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (Vol. 2016-May, pp. 794-798). [7471784] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7471784

Classification of respiratory effort and disordered breathing during sleep from audio and pulse oximetry signals. / Snider, Brian R.; Kain, Alexander.

2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Vol. 2016-May Institute of Electrical and Electronics Engineers Inc., 2016. p. 794-798 7471784.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Snider, BR & Kain, A 2016, Classification of respiratory effort and disordered breathing during sleep from audio and pulse oximetry signals. in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. vol. 2016-May, 7471784, Institute of Electrical and Electronics Engineers Inc., pp. 794-798, 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, 3/20/16. https://doi.org/10.1109/ICASSP.2016.7471784

Snider BR, Kain A. Classification of respiratory effort and disordered breathing during sleep from audio and pulse oximetry signals. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Vol. 2016-May. Institute of Electrical and Electronics Engineers Inc. 2016. p. 794-798. 7471784 https://doi.org/10.1109/ICASSP.2016.7471784

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