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

A. Kam; A. Cohen; A. B. Geva; A. Tarasiuk

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

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

Research output: Contribution to journal › Conference article › peer-review

18 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 language	English
Pages (from-to)	33-36
Number of pages	4
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	26 I
State	Published - 1 Dec 2004
Event	Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States Duration: 1 Sep 2004 → 5 Sep 2004

Keywords

CD-HMM
GMM
K-complex
Scorers

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Cite this

@article{9c426cc497e84ce7b9639ca32a6ac22c,

title = "Detection of K-complexes in sleep EEG using CD-HMM",

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.",

keywords = "CD-HMM, GMM, K-complex, Scorers",

author = "A. Kam and A. Cohen and Geva, {A. B.} and A. Tarasiuk",

year = "2004",

month = dec,

day = "1",

language = "English",

volume = "26 I",

pages = "33--36",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

publisher = "Institute of Electrical and Electronics Engineers",

note = "Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 ; Conference date: 01-09-2004 Through 05-09-2004",

}

TY - JOUR

T1 - Detection of K-complexes in sleep EEG using CD-HMM

AU - Kam, A.

AU - Cohen, A.

AU - Geva, A. B.

AU - Tarasiuk, A.

PY - 2004/12/1

Y1 - 2004/12/1

N2 - 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.

AB - 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.

KW - CD-HMM

KW - GMM

KW - K-complex

KW - Scorers

UR - http://www.scopus.com/inward/record.url?scp=11044235867&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:11044235867

SN - 0589-1019

VL - 26 I

SP - 33

EP - 36

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004

Y2 - 1 September 2004 through 5 September 2004

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this