Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 신재영 | - |
dc.date.accessioned | 2019-12-01T18:53:01Z | - |
dc.date.available | 2019-12-01T18:53:01Z | - |
dc.date.issued | 2017-11 | - |
dc.identifier.citation | SCIENTIFIC REPORTS, v. 7, Article no. 16545 | en_US |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | https://www.nature.com/articles/s41598-017-16639-0 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/116109 | - |
dc.description.abstract | This study investigated the effectiveness of using a high-density multi-distance source-detector (SD) separations in near-infrared spectroscopy (NIRS), for enhancing the performance of a functional NIRS (fNIRS)-based brain-computer interface (BCI). The NIRS system that was used for the experiment was capable of measuring signals from four SD separations: 15, 21.2, 30, and 33.5 mm, and this allowed the measurement of hemodynamic response alterations at various depths. Fifteen participants were asked to perform mental arithmetic and word chain tasks, to induce task-related hemodynamic response variations, or they were asked to stay relaxed to acquire a baseline signal. To evaluate the degree of BCI performance enhancement by high-density channel configuration, the classification accuracy obtained using a typical low-density lattice SD arrangement, was compared to that obtained using the high-density SD arrangement, while maintaining the SD separation at 30 mm. The analysis results demonstrated that the use of a high-density channel configuration did not result in a noticeable enhancement of classification accuracy. However, the combination of hemodynamic variations, measured by two multi-distance SD separations, resulted in the significant enhancement of overall classification accuracy. The results of this study indicated that the use of high-density multi-distance SD separations can likely provide a new method for enhancing the performance of an fNIRS-BCI. | en_US |
dc.description.sponsorship | This work was partly supported by the ICT R&D program of MSIT/IITP [2017-0-00432, Development of non-invasive integrated BCI SW platform to control home appliances and external devices by user's thought via AR/VR interface], and partly by the Brain Research Program through the National Research Foundation of Korea, funded by the Ministry of Science and ICT (NRF-2015M3C7A1031969). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | NATURE PUBLISHING GROUP | en_US |
dc.subject | NEAR-INFRARED SPECTROSCOPY | en_US |
dc.subject | CLASSIFICATION | en_US |
dc.subject | SIGNALS | en_US |
dc.title | Performance enhancement of a brain-computer interface using high-density multi-distance NIRS | en_US |
dc.type | Article | en_US |
dc.relation.volume | 7 | - |
dc.identifier.doi | 10.1038/s41598-017-16639-0 | - |
dc.identifier.doi | 10.1038/s41598-017-16639-0 | - |
dc.relation.page | 16545-16545 | - |
dc.relation.journal | SCIENTIFIC REPORTS | - |
dc.contributor.googleauthor | Shin, Jaeyoung | - |
dc.contributor.googleauthor | Kwon, Jinuk | - |
dc.contributor.googleauthor | Choi, Jongkwan | - |
dc.contributor.googleauthor | Im, Chang-Hwan | - |
dc.relation.code | 2017003408 | - |
dc.sector.campus | S | - |
dc.sector.daehak | RESEARCH INSTITUTE[S] | - |
dc.sector.department | INSTITUTE OF BIOMEDICAL ENGINEERING | - |
dc.identifier.pid | naraeshigo | - |
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