Camera-Based On-Line Short Cessation of Breathing Detection

Ilde Lorato, Sander Stuijk, Mohammed Meftah, Wim Verkruijsse, Gerard de Haan

ICCVW 2019 pp. 1656-1663

doi:10.1109/ICCVW.2019.00205 /iccvw/2019/lorato2019iccvw-camerabased/

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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Text

Lorato et al. "Camera-Based On-Line Short Cessation of Breathing Detection." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00205

Markdown

[Lorato et al. "Camera-Based On-Line Short Cessation of Breathing Detection." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/lorato2019iccvw-camerabased/) doi:10.1109/ICCVW.2019.00205

BibTeX

@inproceedings{lorato2019iccvw-camerabased,
  title     = {{Camera-Based On-Line Short Cessation of Breathing Detection}},
  author    = {Lorato, Ilde and Stuijk, Sander and Meftah, Mohammed and Verkruijsse, Wim and de Haan, Gerard},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2019},
  pages     = {1656-1663},
  doi       = {10.1109/ICCVW.2019.00205},
  url       = {https://mlanthology.org/iccvw/2019/lorato2019iccvw-camerabased/}
}