Optimal Parameters of Adaptive Segmentation for Epileptic Graphoelements Recognition

Manual review of EEG records, as it is per¬formed in common medical practice, is very time-consuming. There is an effort to make this analysis easier and faster for neurologists by using systems for automatic EEG graphoelements recognition. Such a system is composed of three steps: (1) segmentation, which is a subject of this article, (2) features extraction and (3) classification. Precision of classification, and thereby the whole recognition, is strongly affected by the quality of preceding segmentation procedure, which depends on the method of segmentation and its parameters. In this paper, Varri’s method for segmentation of real epileptic EEG signals is used. Effect of input parameters on segmentation outcome is discussed and parameters values are proposed to achieve optimal outcome suitable for the following classification and graphoelements recognition. Only the results of segmentation are presented in this paper.

Keywords

EEG, adaptive segmentation, epilepsy, two connected windows method

Citation

Radioengineering. 2017 vol. 26, č. 1, s. 323-329. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2017/17_01_0323_0329.pdf

Document type

Peer-reviewed

Document version

Published version

Language of document

en

Document licence

Creative Commons Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/