Presentation	2022-05-26 Fetal arrhythmia detection based on deep learning using fetal ECG signals Sara Nakatani, Kohei Yamamoto, Tomoaki Ohtsuki,
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Abstract(in English)
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Paper #	SeMI2022-6
Date of Issue	2022-05-19 (SeMI)

Conference Information
Committee	SeMI / IPSJ-DPS / IPSJ-MBL / IPSJ-ITS
Conference Date	2022/5/26(2days)
Place (in Japanese)	(See Japanese page)
Place (in English)
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Topics (in English)
Chair	Koji Yamamoto(Kyoto Univ.)
Vice Chair	Kazuya Monden(Hitachi) / Yasunori Owada(NICT)
Secretary	Kazuya Monden(Cyber Univ.) / Yasunori Owada(Waseda Univ.) / (Osaka Univ.)
Assistant	Yuki Katsumata(NTT DOCOMO) / Akihito Taya(Aoyama Gakuin Univ.) / Yu Nakayama(Tokyo Univ. of Agri. and Tech.)

Paper Information
Registration To	Technical Committee on Sensor Network and Mobile Intelligence / Special Interest Group on Distributed Processing System / Special Interest Group on Mobile Computing and Pervasive Systems / Special Interest Group on Intelligent Transport Systems and Smart Community
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Fetal arrhythmia detection based on deep learning using fetal ECG signals
Sub Title (in English)
Keyword(1)
1st Author's Name	Sara Nakatani
1st Author's Affiliation	Keio University(Keio Univ.)
2nd Author's Name	Kohei Yamamoto
2nd Author's Affiliation	Keio University(Keio Univ.)
3rd Author's Name	Tomoaki Ohtsuki
3rd Author's Affiliation	Keio University(Keio Univ.)
Date	2022-05-26
Paper #	SeMI2022-6
Volume (vol)	vol.122
Number (no)	SeMI-46
Page	pp.pp.26-31(SeMI),
#Pages	6
Date of Issue	2022-05-19 (SeMI)