Yamamoto, Shota https://orcid.org/0000-0003-1320-390X
Yanagisawa, Takufumi https://orcid.org/0000-0002-2057-0612
Fukuma, Ryohei
Oshino, Satoru
Tani, Naoki
Khoo, Hui Ming https://orcid.org/0000-0002-4039-0520
Edakawa, Kohtaroh
Kobayashi, Maki
Tanaka, Masataka
Fujita, Yuya
Kishima, Haruhiko https://orcid.org/0000-0002-9041-2337
Funding for this research was provided by:
Japan Society for the Promotion of Science (JP18H04085)
Japan Science and Technology Agency (Moonshot R&D-MILLENNIA Program (JPMJMS2012))
Exploratory Research for Advanced Technology (JPMJER1801)
Core Research for Evolutional Science and Technology (JPMJCR18A5)
Precursory Research for Embryonic Science and Technology (JPMJPR1506)
Japan Agency for Medical Research and Development (19de0107001)
Council for Science, Technology and Innovation (Cross-ministerial Strategic Innovation Promotion P)
Article Title: Data-driven electrophysiological feature based on deep learning to detect epileptic seizures
Journal Title: Journal of Neural Engineering
Article Type: paper
Copyright Information: © 2021 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2021-05-09
Date Accepted: 2021-09-03
Online publication date: 2021-09-30