Characteristic analysis of visual evoked potentials and posterior dominant rhythm by use of EEG model

Kazuhiko Goto, Takenao Sugi, Yoshitaka Matsuda, Satoru Goto, Hiroki Fukuda, Yoshinobu Goto, Takao Yamasaki, Shozo Tobimatsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems
Pages233-236
Number of pages4
DOIs
Publication statusPublished - Dec 1 2013
Event2013 13th International Conference on Control, Automation and Systems, ICCAS 2013 - Gwangju, Korea, Republic of
Duration: Oct 20 2013Oct 23 2013

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833

Other

Other2013 13th International Conference on Control, Automation and Systems, ICCAS 2013
CountryKorea, Republic of
CityGwangju
Period10/20/1310/23/13

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Goto, K., Sugi, T., Matsuda, Y., Goto, S., Fukuda, H., Goto, Y., ... Tobimatsu, S. (2013). Characteristic analysis of visual evoked potentials and posterior dominant rhythm by use of EEG model. In ICCAS 2013 - 2013 13th International Conference on Control, Automation and Systems (pp. 233-236). [6703899] (International Conference on Control, Automation and Systems). https://doi.org/10.1109/ICCAS.2013.6703899