Fully-automatic camera-based pulse-oximetry during sleep

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

10 Citations (Scopus)
486 Downloads (Pure)

Abstract

Current routines for the monitoring of sleep require many sensors attached to the patient during a nocturnal observational study, limiting mobility and causing stress and discomfort. Cameras have shown promise in the remote monitoring of pulse rate, respiration and oxygen saturation, which potentially allows a reduction in the number of sensors. Applying these techniques in a sleep setting is challenging, as it is unknown upfront which portion of the skin will be visible, there is no unique skin-color outside the visible range, and the pulsatility is low in infrared. We present a fully-automatic living tissue detection method to enable continuous monitoring of pulse rate and oxygen saturation during sleep. The system is validated on a dataset where various typical sleep scenarios have been simulated. Results show the proposed method to outperform the current state-of-the-art, especially for the estimation of oxygen saturation.
Original languageEnglish
Title of host publication2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1430-1438
Number of pages9
ISBN (Electronic)978-1-5386-6100-0
DOIs
Publication statusPublished - 13 Dec 2018
Event2018 IEEE conference on computer vision and pattern recognition workshops (CVPR 2018) - Calvin L. Rampton Salt Palace Convention Center, Salt Lake City, United States
Duration: 18 Jun 201822 Jun 2018
http://cvpr2018.thecvf.com

Conference

Conference2018 IEEE conference on computer vision and pattern recognition workshops (CVPR 2018)
Abbreviated titleCVPR 2018
CountryUnited States
CitySalt Lake City
Period18/06/1822/06/18
Internet address

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