TY - GEN
T1 - Characteristic analysis of visual evoked potentials and posterior dominant rhythm by use of EEG model
AU - Goto, Kazuhiko
AU - Sugi, Takenao
AU - Matsuda, Yoshitaka
AU - Goto, Satoru
AU - Fukuda, Hiroki
AU - Goto, Yoshinobu
AU - Yamasaki, Takao
AU - Tobimatsu, Shozo
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Visual evoked potentials (VEPs) are the electrical responses from the brain concerned with visual information processing. Amplitude of VEPs is smaller than that of background EEG activity, and the stimulus-locked averaging method is usually used for obtained the waveform. VEP response to each stimulus is not completely the same however it is varying with its amplitude and duration. Therefore, amplitude of averaged VEP waveform deteriorates due to their variability in raw data. Feature extraction of background EEG activity during visual stimulation is also a one of significant items in VEP analysis. In that case, separation of VEP component and background EEG component (mainly posterior dominant rhythm) is crucial. In the past, we proposed the method of estimating both amplitude of VEP and dominant rhythm by use of EEG model. This present study, the proposed method was applied to actual recorded VEP data and its effectiveness was evaluated. EEGs with visual stimulus were recorded from nine healthy young adults. Usefulness of the proposed method was investigated by comparing the conventional power spectrum averaging method. The proposed method will be applicable to show an accurate VEP analysis and characteristic analysis of background activity under visual stimulus.
AB - Visual evoked potentials (VEPs) are the electrical responses from the brain concerned with visual information processing. Amplitude of VEPs is smaller than that of background EEG activity, and the stimulus-locked averaging method is usually used for obtained the waveform. VEP response to each stimulus is not completely the same however it is varying with its amplitude and duration. Therefore, amplitude of averaged VEP waveform deteriorates due to their variability in raw data. Feature extraction of background EEG activity during visual stimulation is also a one of significant items in VEP analysis. In that case, separation of VEP component and background EEG component (mainly posterior dominant rhythm) is crucial. In the past, we proposed the method of estimating both amplitude of VEP and dominant rhythm by use of EEG model. This present study, the proposed method was applied to actual recorded VEP data and its effectiveness was evaluated. EEGs with visual stimulus were recorded from nine healthy young adults. Usefulness of the proposed method was investigated by comparing the conventional power spectrum averaging method. The proposed method will be applicable to show an accurate VEP analysis and characteristic analysis of background activity under visual stimulus.
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U2 - 10.1109/ICCAS.2013.6703899
DO - 10.1109/ICCAS.2013.6703899
M3 - Conference contribution
AN - SCOPUS:84893616288
SN - 9788993215052
T3 - International Conference on Control, Automation and Systems
SP - 233
EP - 236
BT - ICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems
T2 - 2013 13th International Conference on Control, Automation and Systems, ICCAS 2013
Y2 - 20 October 2013 through 23 October 2013
ER -