Extraction of the Fetal Electrocardiogram Using Dynamic Neural Networks

Bibliographic Details
Parent link:Biomedical Engineering.— , 1967-
Vol. 50, iss. 6.— 2017.— [P. 371–375]
Main Author: Devyatykh D. V. Dmitry Vladimirovich
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт неразрушающего контроля (ИНК) Учебно-методический отдел (УМО)
Other Authors: Gerget O. M. Olga Mikhailovna
Summary:Title screen
This article presents a nonlinear dynamics model for discriminating the sources of the maternal abdominal elec-trocardiogram (aECG). The coefficients of the separating matrix were determined by training a neural network. This method provides efficient extraction of the fetal electrocardiogram (fECG) independently of the choice of recording point, input signal duration, or number of independent leads.
Режим доступа: по договору с организацией-держателем ресурса
Language:English
Published: 2017
Subjects:
Online Access:http://dx.doi.org/10.1007/s10527-017-9658-y
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654338