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Cited 3 time in webofscience Cited 6 time in scopus
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Classification of color imagination using Emotiv EPOC and event-related potential in electroencephalogram

Authors
Yu, Je-HunSim, Kwee-Bo
Issue Date
2016
Publisher
ELSEVIER GMBH, URBAN & FISCHER VERLAG
Keywords
Brain computer interface; Event-related potential (ERP); Arduino; Emotiv EPOC; Artificial neural network
Citation
OPTIK, v.127, no.20, pp 9711 - 9718
Pages
8
Journal Title
OPTIK
Volume
127
Number
20
Start Page
9711
End Page
9718
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/8783
DOI
10.1016/j.ijleo.2016.07.074
ISSN
0030-4026
Abstract
In this paper, we proposed a method that classifies electroencephalography (EEG) from color imagination data using the Emotiv EPOC headset. For EEG measurement and the event-related potential (ERP) method, brain-computer interface (BCI) systems were used in the experiment. In the experiment, the subjects gaze at a non-flicker visual stimulus of color (i.e., red, green, blue, white, and yellow) and then proceed to imagine the color. To concentrate on the LED light, all experiments were performed in a dimly lit room. The flickered visual stimulus was made using an Arduino microcontroller board and LEDs with the purpose of prompting color imagination. As a result, we obtained significant EEG responses of thoughts related to certain colors. The EEG response is classified using classification algorithms including a support vector machine (SVM) with linear discriminant analysis (LDA), an artificial neural network (ANN) with LDA, and an ANN without LDA. In addition, fivefold cross validation was used to evaluate the performance. From the results, we found robust electrodes (T7 and F4). The technology developed in this paper can be used to assist paralyzed individuals and the elderly. (C) 2016 Elsevier GmbH. All rights reserved.
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