An Efficient Adaptive Filter for Fetal ECG Extraction Using Neural Network

Journal of Intelligent Systems 28 (4):589-600 (2019)
  Copy   BIBTEX

Abstract

Fetal electrocardiogram checking is a strategy for acquiring critical data about the state of the fetus during pregnancy and labor. This is done by measuring electrical signals created by the fetal heart as measured from multichannel potential recordings on the mother’s body surface. In any case, extraction of fetal signal is difficult because the signal is marred by the mother’s heartbeat signal. Subsequently, in this paper, a powerful versatile filtering strategy is utilized to eliminate the mother’s heartbeat signal with the specific end goal of extricating the fetal signal. The proposed procedure was executed in the working stage of MATLAB and the execution results were investigated.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 101,757

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Undersampling Aware Learning based Fetal Health Prediction using Cardiotocographic Data.M. Shyamala Devi - 2021 - Turkish Online Journal of Qualitative Inquiry (TOJQI) 12 (6):7730-7749.
On the impairment argument.William Simkulet - 2021 - Bioethics 35 (5):400-406.
A Realistic Approach to Maternal‐Fetal Conflict.Deborah Hornstra - 1998 - Hastings Center Report 28 (5):7-12.
Abortion.Mary Anne Warren - 1998 - In Helga Kuhse & Peter Singer (eds.), A Companion to Bioethics. Malden, Mass., USA: Wiley-Blackwell. pp. 140–148.

Analytics

Added to PP
2017-12-14

Downloads
13 (#1,331,439)

6 months
5 (#1,067,832)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references