NN-based fecg extraction from the composite abdominal ECG

Muhammad Asraful Hasan, Muhammad Ibn Ibrahimy, Md. Mamun Ibne Reaz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labour. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach is to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be considered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG. Copyright

Original languageEnglish
Title of host publication38th International Conference on Computers and Industrial Engineering 2008
Pages2665-2669
Number of pages5
Volume3
Publication statusPublished - 2008
Externally publishedYes

Fingerprint

Electrocardiography
Composite materials
Momentum
Fetal monitoring
Neural networks
Personnel

Keywords

  • Abdominal ECG
  • FECG
  • Heart rate
  • Neural network

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this

Hasan, M. A., Ibrahimy, M. I., & Ibne Reaz, M. M. (2008). NN-based fecg extraction from the composite abdominal ECG. In 38th International Conference on Computers and Industrial Engineering 2008 (Vol. 3, pp. 2665-2669)

NN-based fecg extraction from the composite abdominal ECG. / Hasan, Muhammad Asraful; Ibrahimy, Muhammad Ibn; Ibne Reaz, Md. Mamun.

38th International Conference on Computers and Industrial Engineering 2008. Vol. 3 2008. p. 2665-2669.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hasan, MA, Ibrahimy, MI & Ibne Reaz, MM 2008, NN-based fecg extraction from the composite abdominal ECG. in 38th International Conference on Computers and Industrial Engineering 2008. vol. 3, pp. 2665-2669.
Hasan MA, Ibrahimy MI, Ibne Reaz MM. NN-based fecg extraction from the composite abdominal ECG. In 38th International Conference on Computers and Industrial Engineering 2008. Vol. 3. 2008. p. 2665-2669
Hasan, Muhammad Asraful ; Ibrahimy, Muhammad Ibn ; Ibne Reaz, Md. Mamun. / NN-based fecg extraction from the composite abdominal ECG. 38th International Conference on Computers and Industrial Engineering 2008. Vol. 3 2008. pp. 2665-2669
@inproceedings{28aa6bbd3d134db3a1019e9a37a445d6,
title = "NN-based fecg extraction from the composite abdominal ECG",
abstract = "FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labour. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach is to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be considered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG. Copyright",
keywords = "Abdominal ECG, FECG, Heart rate, Neural network",
author = "Hasan, {Muhammad Asraful} and Ibrahimy, {Muhammad Ibn} and {Ibne Reaz}, {Md. Mamun}",
year = "2008",
language = "English",
isbn = "9781627486828",
volume = "3",
pages = "2665--2669",
booktitle = "38th International Conference on Computers and Industrial Engineering 2008",

}

TY - GEN

T1 - NN-based fecg extraction from the composite abdominal ECG

AU - Hasan, Muhammad Asraful

AU - Ibrahimy, Muhammad Ibn

AU - Ibne Reaz, Md. Mamun

PY - 2008

Y1 - 2008

N2 - FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labour. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach is to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be considered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG. Copyright

AB - FECG (Fetal ECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labour. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this paper is to illustrate the developed algorithms on FECG signal extraction from the abdominal ECG signal using Neural Network approach is to provide efficient and effective ways of separating and understanding the FECG signal and its nature. The FECG signal was isolated from the abdominal signal by neural network approach with different learning constant value and momentum as well so that acceptable signal can be considered. According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. The method appears to be exceedingly robust, correctly isolate the FECG signal from abdominal ECG. Copyright

KW - Abdominal ECG

KW - FECG

KW - Heart rate

KW - Neural network

UR - http://www.scopus.com/inward/record.url?scp=84860140452&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860140452&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84860140452

SN - 9781627486828

VL - 3

SP - 2665

EP - 2669

BT - 38th International Conference on Computers and Industrial Engineering 2008

ER -