Performance enhancement of a brain-computer interface using high-density multi-distance NIRS

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 expe...

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Autores principales:	Jaeyoung Shin, Jinuk Kwon, Jongkwan Choi, Chang-Hwan Im
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5f0b0849e741491cbe931733ac017b88
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spelling	oai:doaj.org-article:5f0b0849e741491cbe931733ac017b882021-12-02T15:04:58ZPerformance enhancement of a brain-computer interface using high-density multi-distance NIRS10.1038/s41598-017-16639-02045-2322https://doaj.org/article/5f0b0849e741491cbe931733ac017b882017-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-16639-0https://doaj.org/toc/2045-2322Abstract 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.Jaeyoung ShinJinuk KwonJongkwan ChoiChang-Hwan ImNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jaeyoung Shin Jinuk Kwon Jongkwan Choi Chang-Hwan Im Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
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.
format	article
author	Jaeyoung Shin Jinuk Kwon Jongkwan Choi Chang-Hwan Im
author_facet	Jaeyoung Shin Jinuk Kwon Jongkwan Choi Chang-Hwan Im
author_sort	Jaeyoung Shin
title	Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
title_short	Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
title_full	Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
title_fullStr	Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
title_full_unstemmed	Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
title_sort	performance enhancement of a brain-computer interface using high-density multi-distance nirs
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/5f0b0849e741491cbe931733ac017b88
work_keys_str_mv	AT jaeyoungshin performanceenhancementofabraincomputerinterfaceusinghighdensitymultidistancenirs AT jinukkwon performanceenhancementofabraincomputerinterfaceusinghighdensitymultidistancenirs AT jongkwanchoi performanceenhancementofabraincomputerinterfaceusinghighdensitymultidistancenirs AT changhwanim performanceenhancementofabraincomputerinterfaceusinghighdensitymultidistancenirs
_version_	1718388958630510592

Performance enhancement of a brain-computer interface using high-density multi-distance NIRS

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