Sleep Spindle Detection in EEG Signals Combining HMMs and SVMs

  • Iosif Mporas
  • Panagiotis Korvesis
  • Evangelia I. Zacharaki
  • Vasilis Megalooikonomou
Part of the Communications in Computer and Information Science book series (CCIS, volume 384)

Abstract

In this paper we present a combined SVM-HMM sleep spindle detection scheme. The proposed scheme takes advantage of the information provided from each of the two prediction models in decision level, in order to provide refined and more accurate spindle detection results. The experimental results showed that the proposed combined scheme achieved an overall detection performance of 90.28%, increasing the best-performing SVM-based model by 2% in terms of absolute performance.

Keywords

sleep spindles EEG support vector machines hidden Markov models 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Iosif Mporas
    • 1
  • Panagiotis Korvesis
    • 1
  • Evangelia I. Zacharaki
    • 1
  • Vasilis Megalooikonomou
    • 1
  1. 1.Department of Computer Engineering & InformaticsUniversity of PatrasPatrasGreece

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