Obstructive sleep apnea detection using SVM-based classification of ECG signal features

  title={Obstructive sleep apnea detection using SVM-based classification of ECG signal features},
  author={Laiali Almazaydeh and Khaled M. Elleithy and Miad Faezipour},
  journal={2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
Sleep apnea is the instance when one either has pauses of breathing in their sleep, or has very low breath while asleep. This pause in breathing can range in frequency and duration. Obstructive sleep apnea (OSA) is the common form of sleep apnea, which is currently tested through polysomnography (PSG) at sleep labs. PSG is both expensive and inconvenient as an expert human observer is required to work over night. New sleep apnea classification techniques are nowadays being developed by… CONTINUE READING
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Detection of Obstructive Sleep Apnoeaa at Different Time Scales Using the Electrocardiogram,

  • P. Chazal, T. Penzel, C. Heneghan, “Automated
  • Institute of Physics Publishing,
  • 2004
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Spectral Analysis of Electroencephalogram and Oximetric Signals in Obstructive Sleep Apnea Diagnosis

  • D. Avarez, R. Hornero, J. Marcos, F. Campo, M. Lopez
  • Proceedings of the 31 IEEE International…
  • 2009
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