Determination of the Concentrated State Using Multiple EEG Channels
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Determination of the Concentrated State Using Multiple EEG Channels

Authors: Tae Jin Choi, Jong Ok Kim, Sang Min Jin, Gilwon Yoon

Abstract:

Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (Fp1 and Fp2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that Fp1 and Fp2 are promising locations for extracting control signal for HMI applications.

Keywords: Concentration, EEG, human machine interface.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1094393

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[1] L. Kirkup, A. Searle, A. Craig, P. Mclsaac, and P. Moses, "EEG-based system for rapid on-off switching without prior learning",Medical and Biological Engineering and Computing, vol. 35, pp. 504-509, 1994.
[2] J. R. Wolpaw, D. J. McFarland, "Multichannel EEG-based brain-computer communication,” Electroenceph. clin. Neurophysiol, vol. 90, pp. 444-449, 1994.
[3] B. Blankertz, F. Losch, M. Krauledat, G. Dornhege, G. Curio, K. R. Muller, "The Berlin Brain-Computer Interface: Accurate Performance From First-Session in BCI-NaÏve Subjects,” Biomedical Engineering, IEEE Transactions on, Vol. 55, No. 10, pp. 2452-2462, October 2008.
[4] B-K Kangand G. Yoon,"Generation of Control Signal based on Concentration Detection using EEG signal”, Journal of The Institute of Electronics Engineers of Korea,vol. 50, no. 12, pp. 3193-3196, December 2013.
[5] S-Y Lee and C. Lee "Research on the Game for increasing intensive power using EEG signal”, Department of Computer Science,The Graduate School of Industrial information,Woosong University , pp. 7-41, January 2009.
[6] G. Li, and W-Y Chung, "A Pilot Study on the use of Electroencephalography Sensors for Measuring the Eyelid Closure Degree” Department of Electronic Engineering, Pukyong National University Busan, Korea, pp. 2-4,2013.
[7] J-Y Shim and B-J Ko,"Effects of Brain Development Program for Improving Self-regulation and Concentration in Youth”,Korean journal of youth studies,vol.16, no.9, October 2009.
[8] S. Y. Chung, H. J. Yoon ,"Analysis of Electroencephalogram Electrode Position and Spectral Feature for Emotion Recognition”,Journal of the Society of Korea Industrial and Systems Engineering,vol. 35, no. 2, pp.64-70, June 2012.
[9] Y. Sung, K. Cho, andK. Um, "A Framework for Processing Brain Waves Used in a Brain-computer Interface”, Journalof Information Processing Systems, vol.8, no.2, June 2012.
[10] E-Y Lee, "The effects of musical stimulus on EEG spectra of listeners”, Major of Clinical Music Therapy, Graduate School of Music Therapy, Sookmyung Women’s University, pp. 9-34, December 2004