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arXiv · 1910.04725

Non-contact Infant Sleep Apnea Detection

Gihan Jayatilaka·Harshana Weligampola·Suren Sritharan·Pankayraj Pathmanathan·Roshan Ragel·Isuru Nawinne
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Abstract

Sleep apnea is a breathing disorder where a person repeatedly stops breathing in sleep. Early detection is crucial for infants because it might bring long term adversities. The existing accurate detection mechanism (pulse oximetry) is a skin contact measurement. The existing non-contact mechanisms (acoustics, video processing) are not accurate enough. This paper presents a novel algorithm for the detection of sleep apnea with video processing. The solution is non-contact, accurate and lightweight enough to run on a single board computer. The paper discusses the accuracy of the algorithm on real data, advantages of the new algorithm, its limitations and suggests future improvements.

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Gihan Jayatilaka, Harshana Weligampola, Suren Sritharan, Pankayraj Pathmanathan, Roshan Ragel, Isuru Nawinne. 2019-10-10. Non-contact Infant Sleep Apnea Detection. https://doi.org/10.1109/iciis47346.2019.9063269

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