| Paper Abstract and Keywords |
| Presentation |
2022-01-23 10:55
Fetal Heart Rate Detection via Maternal ECG Cancellation by Neural-Network Autoencoder Abuzar Ahmad Qureshi, Lu Wang, Tomoaki Ohtsuki (Keio Univ.), Kazunari Owada, Hayato Hayashi (Atom Medical Co.) NLP2021-123 MICT2021-98 MBE2021-84 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Fetal heart rate (HR) monitoring is necessary for accessing the state of the fetus during pregnancy and labor. Non-invasive electrodes are used to acquire the abdominal ECG recording. The abdominal ECG not only contains the fetal ECG but also the maternal ECG and other undesirable signals generated due to body motion activity and muscle contractions. Since the most significant contamination is due to the maternal ECG, in this paper, we propose a framework for estimating fetal HR from non-invasively acquired abdominal ECG recordings. We focus on the cancellation of maternal ECG by a neural-network autoencoder that attempts to reconstruct the maternal ECG. Experiments performed on clinically-acquired subjects’ recordings demonstrate the superiority of the proposed method, in terms of fetal heart rate estimation when compared to conventional methods. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Fetal electrocardiography / Heart rate detection / Blind source separation / Neural networks / Autoencoder / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 121, no. 336, MICT2021-98, pp. 243-247, Jan. 2022. |
| Paper # |
MICT2021-98 |
| Date of Issue |
2022-01-14 (NLP, MICT, MBE) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
NLP2021-123 MICT2021-98 MBE2021-84 |
| Conference Information |
| Committee |
NLP MICT MBE NC |
| Conference Date |
2022-01-21 - 2022-01-23 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Online |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
|
| Paper Information |
| Registration To |
MICT |
| Conference Code |
2022-01-NLP-MICT-MBE-NC |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Fetal Heart Rate Detection via Maternal ECG Cancellation by Neural-Network Autoencoder |
| Sub Title (in English) |
|
| Keyword(1) |
Fetal electrocardiography |
| Keyword(2) |
Heart rate detection |
| Keyword(3) |
Blind source separation |
| Keyword(4) |
Neural networks |
| Keyword(5) |
Autoencoder |
| Keyword(6) |
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| Keyword(7) |
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| 1st Author's Name |
Abuzar Ahmad Qureshi |
| 1st Author's Affiliation |
Keio University (Keio Univ.) |
| 2nd Author's Name |
Lu Wang |
| 2nd Author's Affiliation |
Keio University (Keio Univ.) |
| 3rd Author's Name |
Tomoaki Ohtsuki |
| 3rd Author's Affiliation |
Keio University (Keio Univ.) |
| 4th Author's Name |
Kazunari Owada |
| 4th Author's Affiliation |
Atom Medical Corporation (Atom Medical Co.) |
| 5th Author's Name |
Hayato Hayashi |
| 5th Author's Affiliation |
Atom Medical Corporation (Atom Medical Co.) |
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| Speaker |
Author-1 |
| Date Time |
2022-01-23 10:55:00 |
| Presentation Time |
25 minutes |
| Registration for |
MICT |
| Paper # |
NLP2021-123, MICT2021-98, MBE2021-84 |
| Volume (vol) |
vol.121 |
| Number (no) |
no.335(NLP), no.336(MICT), no.337(MBE) |
| Page |
pp.243-247 |
| #Pages |
5 |
| Date of Issue |
2022-01-14 (NLP, MICT, MBE) |