University of Hertfordshire

By the same authors

Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Original languageEnglish
Title of host publication2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467379830
DOIs
Publication statusPublished - 28 Dec 2015
Externally publishedYes
Event15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015 - Belgrade, Serbia
Duration: 2 Nov 20154 Nov 2015

Publication series

Name2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015

Conference

Conference15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015
CountrySerbia
CityBelgrade
Period2/11/154/11/15

Abstract

In this paper, we propose a computationally efficient method to estimate the optimal order of the autoregressive (AR) modeling of electroencephalographic (EEG) signals in order to use the AR coefficients as features for the analysis of EEG signals and the automatic detection of epileptic seizures. The estimation of the optimal AR-order is made using regression analysis of statistical features extracted from the samples of the EEG signals. The proposed method was evaluated in both background and ictal EEG segments using recordings from 10 epileptic patients. The experimental evaluation showed that the mean absolute error of the estimated optimal AR order is approximately 4 units.

ID: 19523820