Classifying neuro-biological signals by evolutionary fuzzy classifier construction

In this research, EOG (electrooculogram) signal was analyzed to predict a subject's intention using a fuzzy classifier. The fuzzy classifier was built automatically based on EOG data by evolutionary algorithm. For automatic fuzzy classifier construction without any experts' knowledge, a ne...

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Bibliographic Details
Published inSICE 2004 Annual Conference : 4-6 August 2004 Vol. 2; pp. 1813 - 1818 vol. 2
Main Authors KIM, Min-Soeng, KIM, Chang-Hyun, LEE, Ju-Jang
Format Conference Proceeding
LanguageEnglish
Published Tokyo IEEE 2004
Society of Instrument and Control Engineers
Subjects
Biological and medical sciences
Biological control systems
Biological system modeling
Computer interfaces
Electrodiagnosis. Electric activity recording
Electrooculography
Electrooculography. Electroretinography
Evolutionary computation
Fuzzy sets
Humans
Instruments
Investigative techniques, diagnostic techniques (general aspects)
Medical sciences
Signal analysis
Signal processing
Fuzzy logic
Electrooculography
Data analysis
Automatic classification
Membership function
Value function
Evolutionary algorithm
Intention
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ISBN9784907764227
4907764227

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Summary:In this research, EOG (electrooculogram) signal was analyzed to predict a subject's intention using a fuzzy classifier. The fuzzy classifier was built automatically based on EOG data by evolutionary algorithm. For automatic fuzzy classifier construction without any experts' knowledge, a new evolutionary algorithm is proposed. A new representation scheme, a new fitness function and adequate evolutionary operators were designed for the proposed evolutionary algorithm. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts, simultaneously. It is shown that the fuzzy classifier built by the proposed algorithm can classify the given EOG data efficiently. As consequence, the fuzzy classifier can recognize the intention of a human subject.
ISBN:9784907764227
4907764227