Influence of stimuli colour on feature classification for BCI applications. (1st January 2014)

• Record Type: Journal Article
• Authors: Singla, Rajesh Kumar; Khosla, Arun; Jha, R.
• Is Part Of: International journal of biomedical engineering and technology. Volume 15:Number 1(2014)
• Page Start: 82
• Page End: 93
• Publication Date: 2014-01-01
• Subjects: BCI -- brain computer interface -- EEG -- electroencephalography -- wavelet transform -- steady-state visual evoked potential -- SVM -- support vector machines; Biomedical engineering -- Periodicals; 610.28
• Languages: English
• ISSNs: 1752-6418

Abstract

One of the key points of Brain Computer Interface (BCI) system is how different Electroencephalogram (EEG) features are abstracted and distinguished. Therefore, EEG signal processing method is the focus of BCI. In this study, 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. Four stimuli colours, green, red, blue and violet, were used in this study to investigate the influence of colour on SSVEPs. The EEG signals recorded from the occipital region were segmented into 1 second windows and features were extracted by using wavelet transform. Support Vector Machines (SVMs) are used for classification. In colour comparison, SSVEP with the violet colour showed higher accuracy than that with other stimuli.