EEG-based usability assessment of 3D shutter glasses
DC Field | Value | Language |
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dc.contributor.author | Wenzel, Markus A. | - |
dc.contributor.author | Schultze-Kraft, Rafael | - |
dc.contributor.author | Meinecke, Frank C. | - |
dc.contributor.author | Cardinaux, Fabien | - |
dc.contributor.author | Kemp, Thomas | - |
dc.contributor.author | Mueller, Klaus-Robert | - |
dc.contributor.author | Curio, Gabriel | - |
dc.contributor.author | Blankertz, Benjamin | - |
dc.date.accessioned | 2021-09-04T03:24:21Z | - |
dc.date.available | 2021-09-04T03:24:21Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2016-02 | - |
dc.identifier.issn | 1741-2560 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/89626 | - |
dc.description.abstract | Objective. Neurotechnology can contribute to the usability assessment of products by providing objective measures of neural workload and can uncover usability impediments that are not consciously perceived by test persons. In this study, the neural processing effort imposed on the viewer of 3D television by shutter glasses was quantified as a function of shutter frequency. In particular, we sought to determine the critical shutter frequency at which the 'neural flicker' vanishes, such that visual fatigue due to this additional neural effort can be prevented by increasing the frequency of the system. Approach. Twenty-three participants viewed an image through 3D shutter glasses, while multichannel electroencephalogram (EEG) was recorded. In total ten shutter frequencies were employed, selected individually for each participant to cover the range below, at and above the threshold of flicker perception. The source of the neural flicker correlate was extracted using independent component analysis and the flicker impact on the visual cortex was quantified by decoding the state of the shutter from the EEG. Main Result. Effects of the shutter glasses were traced in the EEG up to around 67. Hz-about 20. Hz over the flicker perception threshold-and vanished at the subsequent frequency level of 77. Hz. Significance. The impact of the shutter glasses on the visual cortex can be detected by neurotechnology even when a flicker is not reported by the participants. Potential impact. Increasing the shutter frequency from the usual 50. Hz or 60. Hz to 77. Hz reduces the risk of visual fatigue and thus improves shutter-glass-based 3D usability. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IOP PUBLISHING LTD | - |
dc.subject | VISUAL-EVOKED POTENTIALS | - |
dc.subject | STEREOSCOPIC IMAGES | - |
dc.subject | FLICKER | - |
dc.subject | CLASSIFICATION | - |
dc.subject | RESPONSES | - |
dc.subject | RHYTHM | - |
dc.title | EEG-based usability assessment of 3D shutter glasses | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Mueller, Klaus-Robert | - |
dc.identifier.doi | 10.1088/1741-2560/13/1/016003 | - |
dc.identifier.scopusid | 2-s2.0-84957818532 | - |
dc.identifier.wosid | 000371570200004 | - |
dc.identifier.bibliographicCitation | JOURNAL OF NEURAL ENGINEERING, v.13, no.1 | - |
dc.relation.isPartOf | JOURNAL OF NEURAL ENGINEERING | - |
dc.citation.title | JOURNAL OF NEURAL ENGINEERING | - |
dc.citation.volume | 13 | - |
dc.citation.number | 1 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Neurosciences & Neurology | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
dc.relation.journalWebOfScienceCategory | Neurosciences | - |
dc.subject.keywordPlus | VISUAL-EVOKED POTENTIALS | - |
dc.subject.keywordPlus | STEREOSCOPIC IMAGES | - |
dc.subject.keywordPlus | FLICKER | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | RESPONSES | - |
dc.subject.keywordPlus | RHYTHM | - |
dc.subject.keywordAuthor | 3D shutter glasses | - |
dc.subject.keywordAuthor | single-trial classification | - |
dc.subject.keywordAuthor | EEG | - |
dc.subject.keywordAuthor | flicker | - |
dc.subject.keywordAuthor | independent component analysis | - |
dc.subject.keywordAuthor | machine learning | - |
dc.subject.keywordAuthor | neurotechnology | - |
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