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DC Field | Value | Language |
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dc.contributor.author | Dechwechprasit P. | |
dc.contributor.author | Phothisonothai M. | |
dc.contributor.author | Tantisatirapong S. | |
dc.date.accessioned | 2021-04-05T03:22:26Z | - |
dc.date.available | 2021-04-05T03:22:26Z | - |
dc.date.issued | 2017 | |
dc.identifier.other | 2-s2.0-85015875137 | |
dc.identifier.uri | https://ir.swu.ac.th/jspui/handle/123456789/13148 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015875137&doi=10.1109%2fBMEiCON.2016.7859643&partnerID=40&md5=0fbf21e00f52dd63b9c604a26379d91d | |
dc.description.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. | |
dc.subject | Bioelectric potentials | |
dc.subject | Biomedical engineering | |
dc.subject | Brain | |
dc.subject | Electroencephalography | |
dc.subject | Flickering | |
dc.subject | Frequency response | |
dc.subject | Interface states | |
dc.subject | Interfaces (computer) | |
dc.subject | Classification accuracy | |
dc.subject | Constant frequency | |
dc.subject | Electroencephalogram signals | |
dc.subject | Specific frequencies | |
dc.subject | Steady state visual evoked potentials | |
dc.subject | Steady state visually evoked potentials | |
dc.subject | Three parameters | |
dc.subject | Time frequency analysis | |
dc.subject | Brain computer interface | |
dc.title | Time-frequency analysis of red-green visual flickers based on steady-state visual evoked potential recording | |
dc.type | Conference Paper | |
dc.rights.holder | Scopus | |
dc.identifier.bibliograpycitation | BMEiCON 2016 - 9th Biomedical Engineering International Conference. (2017) | |
dc.identifier.doi | 10.1109/BMEiCON.2016.7859643 | |
Appears in Collections: | Scopus 1983-2021 |
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