Detection of K-complexes in sleep EEG using CD-HMM

A. Kam, A. Cohen, A. B. Geva, A. Tarasiuk

Research output: Contribution to journalConference articlepeer-review

15 Scopus citations

Abstract

In the current paper a new approach for K-complex detection using a Continuous Density Hidden Markov Model (CD-HMM) is presented. The system performance was evaluated in two manners. First using three seconds long segments of K-complexes and of background EEG (classification problem). Second using a whole night record and detecting the K complexes (detection problem). The fist test achieved an equal error rate of 7%. In the second test the system performance was compared to four trained scores that scored the signal independently. The performance of the algorithm was within the variance of the human scorers.

Original languageEnglish
Pages (from-to)33-36
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 I
StatePublished - 1 Dec 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: 1 Sep 20045 Sep 2004

Keywords

  • CD-HMM
  • GMM
  • K-complex
  • Scorers

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