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http://dx.doi.org/10.5762/KAIS.2014.15.4.2170

Features of EEG Signal during Attentional Status by Independent Component Analysis in Frequency-Domain  

Kim, Byeong-Nam (Graduate School of Biomedical Engineering, Yonsei University)
Yoo, Sun-Kook (Department of Medical Engineering, College of Medicine, Yonsei University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.15, no.4, 2014 , pp. 2170-2178 More about this Journal
Abstract
In this paper, electroencephalographic (EEG) signal of one among subjects measured biosignal with visual evoked stimuli inducing the concentration was analyzed to detect the changes in the attention status during attention task fulfillment from January to February, 2011. The independent component analysis (ICA) was applied to EEG signals to isolate the attention related innate source signal within the brain and Electroculogram (EOG) artifact from measured EEG signals at the scalp. The consecutive accumulation of short time Fourier transformed (STFT) attention source signal with excluded EOG artifact can enhance the regular depiction of EPOCH graph and spectral color map representing time-varying pattern. The extracted attention indices associated with somatosensory rhythm (SMR: 12-15 Hz), and theta wave (4-7 Hz) increase marginally over time. Throughout experimental observation, the ICA with STFT can be used for the assessment of participants' status of attention.
Keywords
Attention; Electroencephalogram(EEG); Event-Related Potential(ERP); Independent Component Analysis(ICA);
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