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

Xiaoli Li, Xin Yao

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)645-652
Number of pages8
JournalLecture Notes in Computer Science
Publication statusPublished - 1 Jan 2005
Event2nd International Conference on Fuzzy Systems and Knowledge Discovery, Aug 27-29, 2005. Changsha, Peoples R China -
Duration: 1 Jan 2005 → …


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