Publication: EEG-based mental fatigue prediction for driving application
| dc.contributor.author | Sitthichai Iampetch | en_US |
| dc.contributor.author | Yunyong Punsawad | en_US |
| dc.contributor.author | Yodchanan Wongsawat | en_US |
| dc.contributor.other | Mahidol University | en_US |
| dc.date.accessioned | 2018-06-11T04:47:13Z | |
| dc.date.available | 2018-06-11T04:47:13Z | |
| dc.date.issued | 2012-12-01 | en_US |
| dc.description.abstract | Mental fatigue prediction using the electroencephalogram (EEG) has widely been studied. EEG definitely changes when one feels fatigue. However, the challenge is that the accurate results of fatigue prediction are from how to select the EEG interval of interest for real-time prediction. This paper proposes a novel method for efficiently selecting the EEG signal during fatigue period. Eye-blinking (EB) signs detected via the electrooculogram (EOG) are employed as the marker. The EEG band powers are further extracted as the features. The results illustrate that the proposed marker is possible to be efficiently used to predict the mental fatigue state in real-time. ©2012 IEEE. | en_US |
| dc.identifier.citation | 5th 2012 Biomedical Engineering International Conference, BMEiCON 2012. (2012) | en_US |
| dc.identifier.doi | 10.1109/BMEiCon.2012.6465505 | en_US |
| dc.identifier.other | 2-s2.0-84875092026 | en_US |
| dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/14111 | |
| dc.rights | Mahidol University | en_US |
| dc.rights.holder | SCOPUS | en_US |
| dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84875092026&origin=inward | en_US |
| dc.subject | Engineering | en_US |
| dc.title | EEG-based mental fatigue prediction for driving application | en_US |
| dc.type | Conference Paper | en_US |
| dspace.entity.type | Publication | |
| mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84875092026&origin=inward | en_US |