Open-Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping
DC Field | Value | Language |
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dc.contributor.author | Bak, SuJin | - |
dc.contributor.author | Park, Jinwoo | - |
dc.contributor.author | Shin, Jaeyoung | - |
dc.contributor.author | Jeong, Jichai | - |
dc.date.accessioned | 2021-08-31T22:53:04Z | - |
dc.date.available | 2021-08-31T22:53:04Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2019-12 | - |
dc.identifier.issn | 2079-9292 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/61475 | - |
dc.description.abstract | Numerous open-access electroencephalography (EEG) datasets have been released and widely employed by EEG researchers. However, not many functional near-infrared spectroscopy (fNIRS) datasets are publicly available. More fNIRS datasets need to be freely accessible in order to facilitate fNIRS studies. Toward this end, we introduce an open-access fNIRS dataset for three-class classification. The concentration changes of oxygenated and reduced hemoglobin were measured, while 30 volunteers repeated each of the three types of overt movements (i.e., left- and right-hand unilateral complex finger-tapping, foot-tapping) for 25 times. The ternary support vector machine (SVM) classification accuracy obtained using leave-one-out cross-validation was estimated at 70.4% +/- 18.4% on average. A total of 21 out of 30 volunteers scored a superior binary SVM classification accuracy (left-hand vs. right-hand finger-tapping) of over 80.0%. We believe that the introduced fNIRS dataset can facilitate future fNIRS studies. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | NEAR-INFRARED SPECTROSCOPY | - |
dc.subject | BRAIN-COMPUTER-INTERFACE | - |
dc.subject | MOTOR IMAGERY | - |
dc.subject | HEMODYNAMIC-RESPONSES | - |
dc.subject | NIRS | - |
dc.subject | CORTEX | - |
dc.subject | ACTIVATION | - |
dc.subject | PERFORMANCE | - |
dc.subject | SELECTION | - |
dc.subject | PATTERNS | - |
dc.title | Open-Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeong, Jichai | - |
dc.identifier.doi | 10.3390/electronics8121486 | - |
dc.identifier.scopusid | 2-s2.0-85076617234 | - |
dc.identifier.wosid | 000506678200112 | - |
dc.identifier.bibliographicCitation | ELECTRONICS, v.8, no.12 | - |
dc.relation.isPartOf | ELECTRONICS | - |
dc.citation.title | ELECTRONICS | - |
dc.citation.volume | 8 | - |
dc.citation.number | 12 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.subject.keywordPlus | NEAR-INFRARED SPECTROSCOPY | - |
dc.subject.keywordPlus | BRAIN-COMPUTER-INTERFACE | - |
dc.subject.keywordPlus | MOTOR IMAGERY | - |
dc.subject.keywordPlus | HEMODYNAMIC-RESPONSES | - |
dc.subject.keywordPlus | NIRS | - |
dc.subject.keywordPlus | CORTEX | - |
dc.subject.keywordPlus | ACTIVATION | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | SELECTION | - |
dc.subject.keywordPlus | PATTERNS | - |
dc.subject.keywordAuthor | brain-computer interfaces | - |
dc.subject.keywordAuthor | functional near-infrared spectroscopy | - |
dc.subject.keywordAuthor | open-access dataset | - |
dc.subject.keywordAuthor | finger-tapping | - |
dc.subject.keywordAuthor | foot-tapping | - |
dc.subject.keywordAuthor | three-class | - |
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