シオザワ トモキ
SHIOZAWA Tomoki
塩澤 友規 所属 青山学院大学 経営学部 経営学科 職種 教授 |
|
言語種別 | 英語 |
発行・発表の年月 | 2023/11 |
形態種別 | 学術雑誌 |
査読 | 査読あり |
標題 | A Study on Variational Autoencoder to Extract Characteristic Patterns from Electroencephalograms and Electrogastrograms. |
執筆形態 | 共同 |
掲載誌名 | HCI International 2023 – Late Breaking Papers |
掲載区分 | 国外 |
巻・号・頁 | pp.168-178 |
総ページ数 | 11 |
著者・共著者 | Nakane K., Sugie R., Nakayama M., Matsuura Y., Shiozawa T., Hiroki Takada |
概要 | Abstract
Autoencoder (AE) is known as an artificial intelligence (AI), which is considered to be useful to analyze the bio-signal (BS) and/or conduct simulations of the BS. We can show examples to study Electrogastrograms (EGGs) and Electroencephalograms (EEGs) as a BS. In previous study, we have analyzed the EGGs by using the AE and have compared mathematical models of EGGs in the seated posture with those in the supine. The EEGs of normal subjects and patients with Meniere’s disease were herein converted to lower dimensions using Variational AE (VAE). The existence of characteristic differences was verified. |
researchmap用URL | https://link.springer.com/chapter/10.1007/978-3-031-48038-6_11 |