EEG Alpha Activity Detection by Fuzzy Reasoning

E. Huupponen; M. Lehtokangas; J. Saarinen; A. Värri; A. Saastamoinen; S-L. Himanen; J. Hasan

EEG Alpha Activity Detection by Fuzzy Reasoning

E. Huupponen, M. Lehtokangas, J. Saarinen, A. Värri, A. Saastamoinen, S-L. Himanen, J. Hasan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

Automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the presented detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector with four modifications was assessed with ROC curves. When the true positive rate was 85%, the false positive rate was 13%, which is sufficient for sleep EEG analysis.

Original language	English
Title of host publication	Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Vancouver, British Columbia, Canada
Pages	411-416
Number of pages	6
Publication status	Published - 2001
Publication type	A4 Article in conference proceedings
Event	Joint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC, Canada Duration: 25 Jul 2001 → 28 Jul 2001

Conference

Conference	Joint 9th IFSA World Congress and 20th NAFIPS International Conference
Country/Territory	Canada
City	Vancouver, BC
Period	25/07/01 → 28/07/01

Keywords

Automatic detection
EEG alpha
Fuzzy reasoning

Publication forum classification

Publication forum level 0

ASJC Scopus subject areas

Computer Science(all)
Mathematics(all)

Cite this

@inproceedings{2e7aafbe09d14a0ba60c7c5332d3b71a,

title = "EEG Alpha Activity Detection by Fuzzy Reasoning",

abstract = "Automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the presented detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector with four modifications was assessed with ROC curves. When the true positive rate was 85%, the false positive rate was 13%, which is sufficient for sleep EEG analysis.",

keywords = "Automatic detection, EEG alpha, Fuzzy reasoning",

author = "E. Huupponen and M. Lehtokangas and J. Saarinen and A. V{\"a}rri and A. Saastamoinen and S-L. Himanen and J. Hasan",

note = "Tulospisteet 1/2 = TKT ja 1/2 = SGN<br/>Contribution: organisation=tkt,FACT1=0.5<br/>Contribution: organisation=sgn,FACT2=0.5; Joint 9th IFSA World Congress and 20th NAFIPS International Conference ; Conference date: 25-07-2001 Through 28-07-2001",

year = "2001",

language = "English",

pages = "411--416",

booktitle = "Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Vancouver, British Columbia, Canada",

}

Huupponen, E, Lehtokangas, M, Saarinen, J, Värri, A, Saastamoinen, A, Himanen, S-L & Hasan, J 2001, EEG Alpha Activity Detection by Fuzzy Reasoning. in Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Vancouver, British Columbia, Canada. pp. 411-416, Joint 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, BC, Canada, 25/07/01.

EEG Alpha Activity Detection by Fuzzy Reasoning. / Huupponen, E.; Lehtokangas, M.; Saarinen, J. et al.
Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Vancouver, British Columbia, Canada. 2001. p. 411-416.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - EEG Alpha Activity Detection by Fuzzy Reasoning

AU - Huupponen, E.

AU - Lehtokangas, M.

AU - Saarinen, J.

AU - Värri, A.

AU - Saastamoinen, A.

AU - Himanen, S-L.

AU - Hasan, J.

N1 - Tulospisteet 1/2 = TKT ja 1/2 = SGN<br/>Contribution: organisation=tkt,FACT1=0.5<br/>Contribution: organisation=sgn,FACT2=0.5

PY - 2001

Y1 - 2001

N2 - Automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the presented detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector with four modifications was assessed with ROC curves. When the true positive rate was 85%, the false positive rate was 13%, which is sufficient for sleep EEG analysis.

AB - Automated systems are needed to assist the tedious visual analysis of polygraphic recordings. Most systems need detection of different electroencephalogram (EEG) waveforms. The problem in automated detection of alpha activity is the large inter-individual variability of its amplitude and duration. In this work, a fuzzy reasoning based method for the detection of alpha activity was designed and tested. The ranges of the fuzzy rules were determined based on feature statistics. The advantage of the presented detector is that no alpha amplitude threshold needs to be selected. The performance of the alpha detector with four modifications was assessed with ROC curves. When the true positive rate was 85%, the false positive rate was 13%, which is sufficient for sleep EEG analysis.

KW - Automatic detection

KW - EEG alpha

KW - Fuzzy reasoning

M3 - Conference contribution

SP - 411

EP - 416

BT - Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, July 25-28, 2001, Vancouver, British Columbia, Canada

T2 - Joint 9th IFSA World Congress and 20th NAFIPS International Conference

Y2 - 25 July 2001 through 28 July 2001

ER -

EEG Alpha Activity Detection by Fuzzy Reasoning

Abstract

Conference

Keywords

Publication forum classification

ASJC Scopus subject areas

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