| Presentation | 2021-03-03 Automatic Detection of Epileptic Abnormal EEG Using Deep Learning Taku Shoji, Noboru Yoshida, Toshihisa Tanaka, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Although electroencephalography (EEG) is essential for the diagnosis of epilepsy, it requires expertise and experience to evaluate the waveforms. This motivates the need to establish a technology that can automatically detect abnormal EEGs related to epilepsy. In this paper, we propose a compact CNN model for detecting abnormal EEGs. This CNN model has temporal convolution for each electrode, spatial convolution between electrodes, and temporal/space convolution as the primary layers and outputs each electrode's prediction results. This allows us to detect abnormalities in each region of the brain. The simulation results using EEGs of 19 epilepsy patients showed that the proposed model detected abnormal EEGs with AUC and F-values equivalent to or higher than those of existing CNNs. Since the proposed model can efficiently extract features in the temporal and spatial directions with a small number of parameters, it can be applied to detect medical EEG abnormalities in general, where large-scale data is not available. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Epilepsy / Electroencephalogram / Machine learning / Convolutional neural network |
| Paper # | EA2020-62,SIP2020-93,SP2020-27 |
| Date of Issue | 2021-02-24 (EA, SIP, SP) |
| Conference Information | |
| Committee | EA / US / SP / SIP / IPSJ-SLP |
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| Conference Date | 2021/3/3(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Speech, Engineering/Electro Acoustics, Signal Processing, Ultrasonics, and Related Topics |
| Chair | Kenichi Furuya(Oita Univ.) / Hikaru Miura(Nihon Univ.) / Hisashi Kawai(NICT) / Kazunori Hayashi(Kyoto Univ.) / 北岡 教英(豊橋技科大) |
| Vice Chair | Yoshinobu Kajikawa(Kansai Univ.) / Kentaro Matsui(NHK) / Jun Kondo(Shizuoka Univ.) / Yoshikazu Koike(Shibaura Inst. of Tech.) / / Yukihiro Bandou(NTT) / Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) |
| Secretary | Yoshinobu Kajikawa(Univ. of Tokyo) / Kentaro Matsui(NTT) / Jun Kondo(Doshisha Univ.) / Yoshikazu Koike(Tohoku Univ.) / (Univ. of Tokyo) / Yukihiro Bandou(Waseda Univ.) / Toshihisa Tanaka(Hosei Univ.) / (Waseda Univ.) |
| Assistant | Yukou Wakabayashi(Tokyo Metropolitan Univ.) / Tatsuya Komatsu(LINE) / Shinnosuke Hirata(Tokyo Inst. of Tech.) / Yusuke Ijima(NTT) / Yuichi Tanaka(Tokyo Univ. Agri.&Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Engineering Acoustics / Technical Committee on Ultrasonics / Technical Committee on Speech / Technical Committee on Signal Processing / Special Interest Group on Spoken Language Processing |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Automatic Detection of Epileptic Abnormal EEG Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Epilepsy |
| Keyword(2) | Electroencephalogram |
| Keyword(3) | Machine learning |
| Keyword(4) | Convolutional neural network |
| 1st Author's Name | Taku Shoji |
| 1st Author's Affiliation | Tokyo University of Agriculture and Technology(TUAT) |
| 2nd Author's Name | Noboru Yoshida |
| 2nd Author's Affiliation | Department of Pediatrics, Juntendo University Nerima Hospital(Juntendo Univ.) |
| 3rd Author's Name | Toshihisa Tanaka |
| 3rd Author's Affiliation | Tokyo University of Agriculture and Technology(TUAT) |
| Date | 2021-03-03 |
| Paper # | EA2020-62,SIP2020-93,SP2020-27 |
| Volume (vol) | vol.120 |
| Number (no) | EA-397,SIP-398,SP-399 |
| Page | pp.pp.15-20(EA), pp.15-20(SIP), pp.15-20(SP), |
| #Pages | 6 |
| Date of Issue | 2021-02-24 (EA, SIP, SP) |