An Autoencoder-Based Fetal Heart Rate Detector for Noninvasive Recordings

Abuzar Ahmad Qureshi, Lu Wang, Tomoaki Ohtsuki, Kazunari Owada, Naoki Honma, Hayato Hayashi

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Antenatal fetal health monitoring primarily depends on the signal analysis of abdominal or transabdominal electrocardiogram (ECG) recordings. The noninvasive approach for obtaining fetal heart rate (HR) reduces risks of potential infections and is convenient for the expectant mother. However, in addition to strong maternal ECG presence, undesirable signals due to body motion activity, muscle contractions, and certain bio-electric potentials degrade the diagnostic quality of obtained fetal ECG from abdominal ECG recordings. In this paper, we address this problem by proposing an improved framework for estimating fetal HR from non-invasively acquired abdominal ECG recordings. Since the most significant contamination is due to maternal ECG, in the proposed framework, we rely on neural network autoencoder for reconstructing maternal ECG. The autoencoder endeavors to establish the nonlinear mapping between abdominal ECG and maternal ECG thus preserving inherent fetal ECG artifacts. The framework is supplemented with an existing blind-source separation (BSS) algorithm for post-treatment of residual signals obtained after subtracting reconstructed maternal ECG from abdominal ECG. Furthermore, experimental assessments on clinically-acquired subjects' recordings advocate the effectiveness of the proposed framework in comparison with conventional techniques for maternal ECG removal.

本文言語English
ホスト出版物のタイトル43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ60-63
ページ数4
ISBN(電子版)9781728111797
DOI
出版ステータスPublished - 2021
イベント43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
継続期間: 2021 11月 12021 11月 5

出版物シリーズ

名前Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN(印刷版)1557-170X

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
国/地域Mexico
CityVirtual, Online
Period21/11/121/11/5

ASJC Scopus subject areas

  • 信号処理
  • 生体医工学
  • コンピュータ ビジョンおよびパターン認識
  • 健康情報学

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