Publication: Time-frequency analysis of red-green visual flickers based on steady-state visual evoked potential recording
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Issued Date
2017
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-85015875137
Rights Holder(s)
Scopus
Bibliographic Citation
BMEiCON 2016 - 9th Biomedical Engineering International Conference. (2017)
Suggested Citation
Dechwechprasit P., Phothisonothai M., Tantisatirapong S. Time-frequency analysis of red-green visual flickers based on steady-state visual evoked potential recording. BMEiCON 2016 - 9th Biomedical Engineering International Conference. (2017). doi:10.1109/BMEiCON.2016.7859643 Retrieved from: https://hdl.handle.net/20.500.14740/4252
Abstract
The study of brain activity can be done by visual stimulus flickering at specific frequencies, Steady-State Visual Evoked Potential or as known as SSVEP. SSVEP is to stimulate the EEG signal to locate the desired goal of the experiment when a visual stimulus flickering with different constant frequencies and same duration. We aim to present a case study of electroencephalogram (EEG) signal by analyzing the frequency response of the red and green light. The stimulation is based on SSVEP by dividing the trial into two trials: single light and two lights. We considered three parameters that are light color, frequency and epoch interval. The optimal experimental results showed the classification accuracy rate of 74% and 75% for single and two color lights, respectively. The results can be considerably applied to the brain-computer interface (BCI) system. © 2016 IEEE.
Subject(s)
Bioelectric potentials
Biomedical engineering
Brain
Electroencephalography
Flickering
Frequency response
Interface states
Interfaces (computer)
Classification accuracy
Constant frequency
Electroencephalogram signals
Specific frequencies
Steady state visual evoked potentials
Steady state visually evoked potentials
Three parameters
Time frequency analysis
Brain computer interface
Biomedical engineering
Brain
Electroencephalography
Flickering
Frequency response
Interface states
Interfaces (computer)
Classification accuracy
Constant frequency
Electroencephalogram signals
Specific frequencies
Steady state visual evoked potentials
Steady state visually evoked potentials
Three parameters
Time frequency analysis
Brain computer interface