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

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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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Acknowledgements

We would like to acknowledge and thank King Abdulaziz City for Science and Technology (KACST) represented in Grants Programs for Universities and Research Centers (GPURC) for adopting this scientific research under the Graduate Research Program with reference number PS-38-2009 and supporting us with the required hardware. We also thank the sleep medicine and research center (SMRC) at King Abdulaziz University Hospital (KAUH) for their cooperation and support in providing us with the required material and ground truth.

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Authors and Affiliations

  1. FCIT, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Samaher Lashkar & Heyfa Ammar

  2. University of Tunis El Manar, Tunis, Tunisia

    Heyfa Ammar

Authors
  1. Samaher Lashkar
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  2. Heyfa Ammar
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Correspondence to Heyfa Ammar.

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Lashkar, S., Ammar, H. A motion-based waveform for the detection of breathing difficulties during sleep. Machine Vision and Applications 30, 867–874 (2019). https://doi.org/10.1007/s00138-018-0980-5

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  • DOI: https://doi.org/10.1007/s00138-018-0980-5

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