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Feature Extraction and Detection of Obstructive Sleep Apnea from Raw EEG Signal

  • Ch. Usha KumariEmail author
  • Padmavathi Kora
  • K. Meenakshi
  • K. Swaraja
  • T. Padma
  • Asisa Kumar Panigrahy
  • N. Arun Vignesh
Conference paper
  • 25 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1087)

Abstract

Electrocardiogram (EEG) signal detects the electrical activity of the brain. It records all the physiological changes occur in the brain. These signals are useful for detecting different types of sleep disorders. This paper aims in detecting obstructive sleep apnea (OSA) using SVM classifier and DWT technique. The EEG signal is extracted from the polysomnographic database removing the other artifacts, namely electrocardiogram (ECG), blood pressure (BP), respiratory signal at abdominal, respiratory signal at nasal, oxygen saturation are removed. Then, the EEG signal is segmented into four sub-bands as delta(\(\delta \)), theta(\(\theta \)), alpha(\(\alpha \)), and beta(\(\beta \)). The approximation coefficients and detailed coefficients are extracted from these sub-bands using wavelet decomposition technique with Daubechies order-2 (db2) transform. All these coefficients are given to SVM classifier for the detection of OSA. The accuracy of classifier is tested in three cases: in case 1, 90% of data is given for testing; in case 2, 70% is given; and in case 3, only 50% of data is given for testing. It is observed, case 1 has 98% of accuracy in detecting the obstructive sleep apnea. In this paper, 16 healthy subjects and 8 unhealthy subjects are considered. The detailed and approximation coefficients are extracted for all 2500 samples.

Keywords

Electrocardiogram (EEG) Obstructive sleep apnea (osa) Discrete wavelet transform (DWT) Support vector machine (SVM) classifier 

Notes

Acknowledgements

The authors wish to thank the publicly available physio bank database https://physionet.org/physiobank/.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Ch. Usha Kumari
    • 1
    Email author
  • Padmavathi Kora
    • 1
  • K. Meenakshi
    • 1
  • K. Swaraja
    • 1
  • T. Padma
    • 1
  • Asisa Kumar Panigrahy
    • 1
  • N. Arun Vignesh
    • 1
  1. 1.Department of ECEGRIETHyderabadIndia

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