Application of fuzzy similarity to prediction of epileptic seizures using EEG signals

Authors:
Xiaoli Li;Xin Yao
Affiliations:
The Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, The University of Birmingham, Edgbaston, Birmingham, UK;The Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, The University of Birmingham, Edgbaston, Birmingham, UK
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Year:
2005

Citing 1
Cited 1

Similarity measure between fuzzy sets and between elements

Fuzzy Sets and Systems

Application of wavelet-based similarity analysis to epileptic seizures prediction

Computers in Biology and Medicine

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Abstract

The prediction of epileptic seizures is a very attractive issue for all patients suffering from epilepsy in EEG (electroencephalograph) signals. It can assist to develop an intervention system to control / prevent upcoming seizures and change the current treatment method of epilepsy. This paper describes a new method based on wavelet transform and fuzzy similarity measurement to predict the seizures by using EEG signals. One part of the method is to calculate the energy and entropy of EEG data at the different scale; another part of this method is to calculate the similarity between the features set of the reference segment and the test segment using fuzzy measure. The test results of real rats show this method detect temporal dynamic changes prior to a seizure in real time.