期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2013
卷号：3
期号：3
页码：46-52
出版社：International Journal of Soft Computing & Engineering
摘要：This paper presents a Steady State Visual Evoked Potential (SSVEP) based Brain Computer Interface (BCI) system to control a wheelchair in forward, backward, left, right and in stop positions. Four different flickering frequencies in low frequency region were used to elicit the SSVEPs and were displayed on a Liquid Crystal Display (LCD) monitor using LabVIEW. The Electroencephalogram (EEG) signals recorded from the occipital region were first segmented into 1 second window and features were extracted by using Fast Fourier Transform (FFT). Three different classifiers, two based on Artificial Neural Network (ANN) and one based on Support Vector Machine (SVM) were designed and compared to yield better accuracy. Ten subjects were participated in the experiment and the accuracy was calculated by considering the number of correct detections produced while performing a predefined movement sequence. One-Against-All (OAA) based multiclass SVM classifier showed better accuracy than the ANN classifiers
