Automatic sleep stage classification based on ECG and EEG features for day time short nap evaluation

@article{Yu2012AutomaticSS,
  title={Automatic sleep stage classification based on ECG and EEG features for day time short nap evaluation},
  author={Shanshan Yu and Xi Chen and Bei Wang and Xingyu Wang},
  journal={Proceedings of the 10th World Congress on Intelligent Control and Automation},
  year={2012},
  pages={4974-4977}
}
  • Shanshan Yu, Xi Chen, +1 author Xingyu Wang
  • Published in
    Proceedings of the 10th World…
    2012
  • Computer Science
  • In this study, the Electrocardiogram (ECG) and Electroencephalogram (EEG) data recorded during day time short nap were analyzed. The ultimate purpose is to find out effective ECG features combined with usual EEG features for sleep stage determination during day time nap. Firstly, the ECG data was pre-processed in order to eliminate artifacts. After preprocessing, the second-order derivative of the ECG signal was calculated and clustered into two classes by K-means method. The peak positions of… CONTINUE READING

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