Abstract
Concentration is an important part of our life especially during learning or thinking. Visually or auditory evoked concentration affects information processing in human brain. To understand the concentration process of humans, the underlying neural mechanism needs to be explored. EEG device is a promising device to understand underlying neural mechanism of various cognitive functions. In this paper, we propose an accurate concentration monitoring method using a low cost EEG device. Our low cost EEG device has two channel electrodes (FP1, FP2). Usually small channel EEG devices face filtering problem because commonly used filtering method, such as ICA, fails with less number of electrodes. In our work, we investigate effective filters for removing noises from raw data and suitable features for monitoring the concentration status with the low cost EEG device in real time. We collect EEG data from 10 participants for rest state with open eyes and concentration task state. For concentration task, Sudoku game is used. Using support vector machine, we successfully distinguish between rest state and concentration state over 88 % accuracy in real time.
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Emotiv EPOC. https://emotiv.com/epoc.php
Biopac B-alert. http://www.biopac.com/
Quasar DSI system. http://www.quasarusa.com/products_dsi.htm
Gruzelier, J.H.: EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants. Neurosci. Biobehav. Rev. 44, 124––141 (2014)
Gola, M., Magnuski, M., Szumska, I., Wróbel, A.: EEG beta band activity is related to attention and attentional deficits in the visual performance of elderly subjects. Int. J. Psychophysiol. 89(3), 334––341 (2013)
Tonin, L., Leeb, R., Sobolewski, A., del Millán, R.J.: An online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation. J. Neural Eng. 10(5), 056007 (2013)
Lan, T., Adami, A., Erdogmus, D., Pavel, M.: Estimating cognitive state using EEG signals. In: Signal Processing Conference, 2005 13th European. IEEE (2005)
Klimesch, W.: Alpha-band oscillations, attention, and controlled access to stored information. Trends Cogn. Sci. 16(12), 606–617 (2012)
Lubar, J.O., Lubar, J.F.: Electroencephalographic biofeedback of SMR and beta for treatment of attention deficit disorders in a clinical setting. Biofeedback self-Regul. 9(1), 1–23 (1984)
Lee, C., Kwon, J., Kim, G., Hong, K., Shin, D.-S., Lee, D.: A study on EEG based concentration transmission and brain computer interface application. In: The Institute of Electronics Engineers of Korea, pp. 41–46 (2009)
Kannathal, N., Acharya, U.R., Lim, C., Sadasivan, P.: Characterization of EEG—A comparative study. Comput. Methods Programs Biomed. 80(1), 17–23 (2005)
Zhang, Y., Chen, Y., Bressler, S.L., Ding, M.: Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm. Neuroscience 156(1), 238–246 (2008)
Gardner, H.: Frames of mind: The theory of multiple intelligences. Basic books (2011)
Acknowledgements
This work was partly supported by the ICT R&D program of MSIP/IITP. [10041826, Development of emotional features sensing, diagnostics and distribution s/w platform for measurement of multiple intelligence from young children] (50 %) and Regional Specialized Industry R&D program funded by the Ministry of Trade, Industry and Energy(R0002982) (50 %).
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Kang, JS., Ojha, A., Lee, M. (2015). Concentration Monitoring with High Accuracy but Low Cost EEG Device. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9492. Springer, Cham. https://doi.org/10.1007/978-3-319-26561-2_7
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DOI: https://doi.org/10.1007/978-3-319-26561-2_7
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