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Machine Vision and Applications
Published in: Machine Vision and Applications 5/2019

27-09-2018 | Special Issue Paper

A motion-based waveform for the detection of breathing difficulties during sleep

Authors: Samaher Lashkar, Heyfa Ammar

Published in: Machine Vision and Applications | Issue 5/2019

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Abstract

Individuals who suffer from different sleep breathing disorders suffer from a wide range of serious health problems. Unfortunately, the rate of diagnosis is very low, and the existing breathing monitoring techniques are expensive, uncomfortable and time- and labor-intensive. The gold standard PSG is invasive, costly, technically complex and time-consuming. Toward developing a non-contact sleep breathing monitoring system, this study presents a motion-based computer vision approach that aims to detect breathing movements of the sleeping patient from infrared videos and map them into a waveform. The proposed waveform illustrates that each type of breathing difficulty has a specific pattern and hence can be easily distinguished. This facilitates identifying only suspicious periods during which physiological signals will be scored, instead of analyzing the whole signals of 8 h of sleep.
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Metadata
Title
A motion-based waveform for the detection of breathing difficulties during sleep
Authors
Samaher Lashkar
Heyfa Ammar
Publication date
27-09-2018
Publisher
Springer Berlin Heidelberg
Published in
Machine Vision and Applications / Issue 5/2019
Print ISSN: 0932-8092
Electronic ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-018-0980-5

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