Efficient eye blink detection system using RBF classifier

Author

Rihana, Sandy ; Damien, Passerieux ; Moujaess, T.

Author_Institution

Biomed. & Electr. Eng. Dept., USEK, Kaslik, Lebanon

fYear

2012

fDate

28-30 Nov. 2012

Firstpage

360

Lastpage

363

Abstract

Toward an application of brain computer interface, the aim of this paper is to detect eye blink signals from EEG signals. It develops the acquisition using BioRadio portable device and describes the methods used to pre-process these signals, and to classify the eye blinking signals using the Probabilistic Neural Network as a binary classifier. The results obtained are promising, accuracy, selectivity, sensibility and specificity were computed in order to quantify the efficiency of the classification.

Keywords

biomedical equipment; brain-computer interfaces; electroencephalography; eye; medical signal detection; medical signal processing; neurophysiology; probability; signal classification; vision; EEG signals; RBF classifier; binary classifier; bioradio portable device; brain computer interface; eye blink signal detection; probabilistic neural network; signal classification; Accuracy; Biological neural networks; Electroencephalography; Feature extraction; Support vector machine classification; Training; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Circuits and Systems Conference (BioCAS), 2012 IEEE

Conference_Location

Hsinchu

Print_ISBN

978-1-4673-2291-1

Electronic_ISBN

978-1-4673-2292-8

Type

conf

DOI

10.1109/BioCAS.2012.6418422

Filename

6418422