Camera-Based On-Line Short Cessation of Breathing Detection

Ilde Lorato, Sander Stuijk, Mohammed Meftah, Wim Verkruijsse, Gerard de Haan; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 0-0

Abstract


Apnea detection is extremely important in neonatal settings because hypoxia can lead to permanent impairment. Short cessations of breathing are very common in infants and could be used for example for the prediction of longer apneas. The aim of this study is to investigate the accuracy of our on-line cessation of breathing detector. Signals obtained through camera-based respiration monitoring were analyzed in five infants with 91 annotated cessations of breathing. The method proposed is based on the comparison of short-term and long-term standard deviations allowing the detection of sudden amplitude reduction in the signal with a low latency. A new strategy able to detect short cessations of breathing on-line was successfully validated yielding an average accuracy of 93%.

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[bibtex]
@InProceedings{Lorato_2019_ICCV,
author = {Lorato, Ilde and Stuijk, Sander and Meftah, Mohammed and Verkruijsse, Wim and de Haan, Gerard},
title = {Camera-Based On-Line Short Cessation of Breathing Detection},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}