Title :
Efficient eye blink detection system using RBF classifier
Author :
Rihana, Sandy ; Damien, Passerieux ; Moujaess, T.
Author_Institution :
Biomed. & Electr. Eng. Dept., USEK, Kaslik, Lebanon
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;
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
DOI :
10.1109/BioCAS.2012.6418422
