Classification of various facial movement artifacts in EEG signals

Author

Pourzare, Shahin ; Aydemir, Onder ; Kayikcioglu, Temel

Author_Institution

Dept. of Electr. & Electron. Eng., Karadeniz Tech. Univ., Trabzon, Turkey

fYear

2012

fDate

3-4 July 2012

Firstpage

529

Lastpage

533

Abstract

In this paper, a novel approach to classify various facial movement artifacts in EEG signals is presented. EEG signals were obtained in EEG Laboratory from three healthy human subjects in age groups between 28 and 30 years old and on different days. Extracted feature vectors based on root mean square, polynomial fitting and Hjorth descriptors were classified by k-nearest neighbor algorithm. The proposed method was successfully applied to the data sets and achieved an average classification rate of 94% on the test data.

Keywords

electroencephalography; feature extraction; mean square error methods; medical signal processing; polynomials; signal classification; EEG signals; Hjorth descriptors; facial movement artifact classification; feature vector extraction; k-nearest neighbor algorithm; polynomial fitting; root mean square; Accuracy; Classification algorithms; Electroencephalography; Feature extraction; Fitting; Polynomials; Training; Artifact; Classification; EEG; Feature extraction;

fLanguage

English

Publisher

ieee

Conference_Titel

Telecommunications and Signal Processing (TSP), 2012 35th International Conference on

Conference_Location

Prague

Print_ISBN

978-1-4673-1117-5

Type

conf

DOI

10.1109/TSP.2012.6256351

Filename

6256351