|
SHIOZAWA Tomoki
Department Aoyama Gakuin University Department of Business Administration, School of Business Position Professor |
|
| Language | English |
| Publication Date | 2023/11 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | A Study on Variational Autoencoder to Extract Characteristic Patterns from Electroencephalograms and Electrogastrograms. |
| Contribution Type | Collaboration |
| Journal | HCI International 2023 – Late Breaking Papers |
| Journal Type | Another Country |
| Volume, Issue, Page | pp.168-178 |
| Total page number | 11 |
| Author and coauthor | Nakane K., Sugie R., Nakayama M., Matsuura Y., Shiozawa T., Hiroki Takada |
| Details | 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. |
| URL for researchmap | https://link.springer.com/chapter/10.1007/978-3-031-48038-6_11 |