Singular Spectrum Analysis of Sleep EEG in Insomnia

AYDIN S., SARAOĞLU H. M., Kara S.

JOURNAL OF MEDICAL SYSTEMS, vol.35, no.4, pp.457-461, 2011 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 35 Issue: 4
  • Publication Date: 2011
  • Doi Number: 10.1007/s10916-009-9381-7
  • Journal Name: JOURNAL OF MEDICAL SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.457-461
  • Keywords: Sleep EEG, Singular Spectrum Analysis, EEG classification
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

In the present study, the Singular Spectrum Analysis (SSA) is applied to sleep EEG segments collected from healthy volunteers and patients diagnosed by either psycho physiological insomnia or paradoxical insomnia. Then, the resulting singular spectra computed for both C3 and C4 recordings are assigned as the features to the Artificial Neural Network (ANN) architectures for EEG classification in diagnose. In tests, singular spectrum of particular sleep stages such as awake, REM, stage1 and stage2, are considered. Three clinical groups are successfully classified by using one hidden layer ANN architecture with respect to their singular spectra. The results show that the SSA can be applied to sleep EEG series to support the clinical findings in insomnia if ten trials are available for the specific sleep stages. In conclusion, the SSA can detect the oscillatory variations on sleep EEG. Therefore, different sleep stages meet different singular spectra. In addition, different healthy conditions generate different singular spectra for each sleep stage. In summary, the SSA can be proposed for EEG discrimination to support the clinical findings for psycho-psychological disorders.