Yolo4Apnea: Real-time Detection of Obstructive Sleep Apnea

Sondre Hamnvik, Pierre Bernabé, Sagar Sen

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Demos. Pages 5234-5236.

https://doi.org/10.24963/ijcai.2020/754

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Abstract

Obstructive sleep apnea is a serious sleep disorder that affects an estimated one billion adults worldwide. It causes breathing to repeatedly stop and start during sleep which over years increases the risk of hypertension, heart disease, stroke, Alzheimer's, and cancer. In this demo, we present Yolo4Apnea a deep learning system extending You Only Look Once (Yolo) system to detect sleep apnea events from abdominal breathing patterns in real-time enabling immediate awareness and action. Abdominal breathing is measured using a respiratory inductance plethysmography sensor worn around the stomach. The source code is available at https://github.com/simula-vias/Yolo4Apnea

Keywords

  • Machine Learning: general
  • Computer Vision: general
  • Uncertainty in AI: general
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