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Brain State Classification in Epilepsy and Anaesthesia

Transitions between normal and pathological brain states are manifested differently in the electroencephalogram (EEG). Traditional discrimination of these states is often subject to bias and strict definitions. A fuzzy logic-based analysis can permit the classification and tracking of brain states in a non-subjective and unsupervised manner. In this thesis, the combination of fuzzy c-means (FCM) clustering, wavelet, and information theory has revealed notable frequency features in epilepsy and anaesthetic-induced unconsciousness. It was shown that entropy changes in membership functions correlate to specific epileptiform activity and changes in anaesthetic dosages. Seizure episodes appeared in the 31-39 Hz band, suggesting changes in cortical functional organization. The induction of anaesthetics appeared in the 64-72 Hz band, while the return to consciousness appeared in the 32-40 Hz band. Changes in FCM activity were associated with the concentration of anaesthetics. These results can help with the treatment of epilepsy and the safe administration of anaesthesia.

Identiferoai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/25750
Date07 January 2011
CreatorsLee, Angela
ContributorsBardakjian, Berj
Source SetsUniversity of Toronto
Languageen_ca
Detected LanguageEnglish
TypeThesis

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