Real-Time Sleep Apnea Detection by Classifier Combination

@article{Xie2012RealTimeSA,
  title={Real-Time Sleep Apnea Detection by Classifier Combination},
  author={Baile Xie and Hlaing Minn},
  journal={IEEE Transactions on Information Technology in Biomedicine},
  year={2012},
  volume={16},
  pages={469-477}
}
To find an efficient and valid alternative of polysomnography (PSG), this paper investigates real-time sleep apnea and hypopnea syndrome (SAHS) detection based on electrocardiograph (ECG) and saturation of peripheral oxygen (SpO2) signals, individually and in combination. We include ten machine-learning algorithms in our classification experiment. It is shown that our proposed SpO2 features outperform the ECG features in terms of diagnostic ability. More importantly, we propose classifier… CONTINUE READING
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Machine Learning (McGraw Hill Series in Computer Science)

  • T. M. Mitchell
  • New York: McGraw-Hill,
  • 1997
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