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Performance enhancement of a brain-computer interface using high-density multi-distance NIRS
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 wa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5707382/ https://www.ncbi.nlm.nih.gov/pubmed/29185494 http://dx.doi.org/10.1038/s41598-017-16639-0 |
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author | Shin, Jaeyoung Kwon, Jinuk Choi, Jongkwan Im, Chang-Hwan |
author_facet | Shin, Jaeyoung Kwon, Jinuk Choi, Jongkwan Im, Chang-Hwan |
author_sort | Shin, Jaeyoung |
collection | PubMed |
description | 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 | Online Article Text |
id | pubmed-5707382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57073822017-12-06 Performance enhancement of a brain-computer interface using high-density multi-distance NIRS Shin, Jaeyoung Kwon, Jinuk Choi, Jongkwan Im, Chang-Hwan Sci Rep Article 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. Nature Publishing Group UK 2017-11-29 /pmc/articles/PMC5707382/ /pubmed/29185494 http://dx.doi.org/10.1038/s41598-017-16639-0 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Shin, Jaeyoung Kwon, Jinuk Choi, Jongkwan Im, Chang-Hwan Performance enhancement of a brain-computer interface using high-density multi-distance NIRS |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5707382/ https://www.ncbi.nlm.nih.gov/pubmed/29185494 http://dx.doi.org/10.1038/s41598-017-16639-0 |
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