Feature and Model Selection on Automatic Sleep Apnea Detection using ECG

@inproceedings{IsaFeatureAM,
  title={Feature and Model Selection on Automatic Sleep Apnea Detection using ECG},
  author={Sani M. Isa and Mohamad Ivan Fanany and Wisnu Jatmiko and Aniati Murni Murni}
}
The purpose of this study is to find optimal features and classifier's model selection for sleep apnea detection using ECG signals. We want to determine whether a set of unknown ECG signals (test data) is from heavy apnea, mild apnea, or healthy categories. We examine two recent approaches of features selection: an approach proposed by Chazal et al. (2004), which is based on the RR-interval mean and time-series analysis; and an approach proposed by Yilmaz et al. (2010), which is based on the RR… CONTINUE READING

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