| Presentation | 2021-06-29 Proposal of an Analysis Method for fNIRS Using Machine Learning Reiji Ohkuma, Yuto Kurihara, Rieko Osu, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Conventional analysis methods for fNIRS require a large number of parameters in preprocessing, and the analysis results depend on the parameters. We proposed a new analysis method for identifying activated brain regions using fNIRS with a small number of parameters, based on the classification by machine learning and the importance of the features. In this study, we used Random Forest as a machine learning classifier. When we analyzed the brain activity of solving a computational task using the proposed method, the results were similar to those obtained by the conventional analysis method. Although there are some issues to be solved, we believe that the analysis by features importance of machine learning is useful. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | fNIRS / Machine Learning / Features |
| Paper # | NC2021-13,IBISML2021-13 |
| Date of Issue | 2021-06-21 (NC, IBISML) |
| Conference Information | |
| Committee | NC / IBISML / IPSJ-BIO / IPSJ-MPS |
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| Conference Date | 2021/6/28(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Rieko Osu(Waseda Univ.) / Ichiro Takeuchi(Nagoya Inst. of Tech.) / 倉田 博之(九工大) / 関嶋 政和(東工大) |
| Vice Chair | Hiroshi Yamakawa(Univ of Tokyo) / Masashi Sugiyama(Univ. of Tokyo) |
| Secretary | Hiroshi Yamakawa(ATR) / Masashi Sugiyama(NICT) / (Univ. of Tokyo) / (AIST) |
| Assistant | Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU) / Tomoharu Iwata(NTT) / Atsuyoshi Nakamura(Hokkaido Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / Special Interest Group on Bioinformatics and Genomics / Special Interest Group on Mathematical Modeling and Problem Solving |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Proposal of an Analysis Method for fNIRS Using Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | fNIRS |
| Keyword(2) | Machine Learning |
| Keyword(3) | Features |
| 1st Author's Name | Reiji Ohkuma |
| 1st Author's Affiliation | Waseda University(Waseda Univ.) |
| 2nd Author's Name | Yuto Kurihara |
| 2nd Author's Affiliation | Waseda University(Waseda Univ.) |
| 3rd Author's Name | Rieko Osu |
| 3rd Author's Affiliation | Waseda University(Waseda Univ.) |
| Date | 2021-06-29 |
| Paper # | NC2021-13,IBISML2021-13 |
| Volume (vol) | vol.121 |
| Number (no) | NC-79,IBISML-80 |
| Page | pp.pp.91-96(NC), pp.91-96(IBISML), |
| #Pages | 6 |
| Date of Issue | 2021-06-21 (NC, IBISML) |