Migraine analysis through EEG signals with classification approach

Author

Sayyari, Erfan ; Farzi, Mohsen ; Estakhrooeieh, Roohollah Rezaei ; Samiee, Farzaneh ; Shamsollahi, Mohammad Bagher

Author_Institution

Electr. Eng. Dept., Sharif Univ. of Technol., Tehran, Iran

fYear

2012

fDate

2-5 July 2012

Firstpage

859

Lastpage

863

Abstract

Migraine is a common type of headache with neurovascular origin. In this paper, a quantitative analysis of spontaneous EEG patterns is used to examine the migraine patients with maximum and minimum pain levels. The analysis is based on alpha band phase synchronization algorithm. The efficiency of extracted features are examined through one-way ANOVA test. we reached the P-value of 0.0001, proving that the EEG patterns are statistically discriminant in maximum and minimum pain levels. We also used a Neural Network based approach in order to classify the EEG patterns, distinguishing between minimum and maximum pain levels. We achieved the total accuracy of 90.9 %.

Keywords

diseases; electroencephalography; feature extraction; medical signal processing; neural nets; neurophysiology; signal classification; statistical testing; synchronisation; EEG pattern classification; EEG signal; alpha band phase synchronization algorithm; feature extraction; headache; maximum pain level; migraine analysis; migraine patient; minimum pain level; neural network; neurovascular origin; one-way ANOVA test; signal classification; Analysis of variance; Biological neural networks; Electroencephalography; Feature extraction; Pain; Synchronization; EEG; Migraine; Neural Network; Phase Synchronization;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on

Conference_Location

Montreal, QC

Print_ISBN

978-1-4673-0381-1

Electronic_ISBN

978-1-4673-0380-4

Type

conf

DOI

10.1109/ISSPA.2012.6310674

Filename

6310674