• DocumentCode
    636894
  • Title

    Automatic detection of the wake and stage 1 sleep stages using the EEG sub-epoch approach

  • Author

    Malaekah, Emad ; Cvetkovic, Dean

  • Author_Institution
    Sch. of Electr. & Comput. Eng., RMIT Univ., Melbourne, VIC, Australia
  • fYear
    2013
  • fDate
    3-7 July 2013
  • Firstpage
    6401
  • Lastpage
    6404
  • Abstract
    Studies by Rechtschaffen and Kales (R&K), rely on 30-sec epochs to score sleep stages. In this paper, we introduce a new approach based on three consecutive and non-consecutive 6-sec sub-epochs for the detection of the wake stage and stage 1 sleep. The Relative Spectral Energy Band (RSEB) is used as a feature extraction from the electroencephalographic (EEG) signal. Spectral estimation is performed using non-parametric and parametric methods. We then compared the performance of the conventional 30-sec epochs with the three consecutive and non-consecutive 6-sec epochs. The outcomes of this study showed that while the accuracy varies between subjects, the non-parametric method proved to be more effective with stage 1 sleep detection and the parametric method was more effective for wake stage detection. The non-consecutive sub-epoch method was more effective and consecutive method was least effective in non-parametric stage 1 detection. Alternatively, the 30-second epoch method was most effective for parametric wake stage detection.
  • Keywords
    bioelectric potentials; electroencephalography; feature extraction; medical signal detection; medical signal processing; neurophysiology; sleep; electroencephalographic signal; feature extraction; parametric wake stage detection; relative spectral energy band; sleep stage detection; spectral estimation; the EEG sub-epoch approach; Accuracy; Educational institutions; Electroencephalography; Feature extraction; Filtering; Manuals; Sleep;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
  • Conference_Location
    Osaka
  • ISSN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2013.6611019
  • Filename
    6611019