Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation

Conventional techniques are often unable to achieve the Fetal Electrocardiogram FECG extraction and Rpeak detection in FECG from the abdominal ECG (AECG) in satisfactorily level for Fetal Heart Rate (FHR) monitoring. A new methodology by combining the Artificial Neural Network (ANN) and Corr...

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Main Authors: Hasan , M. A., Reaz, Mamun Bin Ibne, Ibrahimy, Muhammad Ibn
Format: Proceeding Paper
Language:English
Published: 2011
Subjects:
Online Access:http://irep.iium.edu.my/6473/
http://irep.iium.edu.my/6473/1/Fetal_electrocardiogram_extraction_and_R-peak_detection_for_fetal_heart_rate_monitoring_using_artificial_neural_network_and_Correlation.pdf
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author Hasan , M. A.
Reaz, Mamun Bin Ibne
Ibrahimy, Muhammad Ibn
author_facet Hasan , M. A.
Reaz, Mamun Bin Ibne
Ibrahimy, Muhammad Ibn
author_sort Hasan , M. A.
building IIUM Repository
collection Online Access
description Conventional techniques are often unable to achieve the Fetal Electrocardiogram FECG extraction and Rpeak detection in FECG from the abdominal ECG (AECG) in satisfactorily level for Fetal Heart Rate (FHR) monitoring. A new methodology by combining the Artificial Neural Network (ANN) and Correlation approach has been proposed in this paper. Artificial Neural Network is chosen primarily since it is adaptive to the nonlinear and time-varying features of the ECG signal. The supervised multilayer perception (MLP) network has been used because it requires a desired output in order to learn. Similarly, the Correlation method has been chosen as the correlation factor can be used to scale the MECG when subtracting it from the AECG, in order to get the FECG. By combining these two approaches the proposed methodology gives better and efficient result in terms of accuracy for FECG extraction and R-peak detection in the AECG signal due to its above characteristics. The proposed approach involves the FECG extraction from the AECG signal with the accuracy of 100% and R-peak detection performance is 93.75%, even though the overlapping situation of MECG and FECG signal in the AECG signal. Therefore the physician and clinician can make the correct decision for the well-being status of the fetus and mother during the pregnancy period.
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institution International Islamic University Malaysia
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language English
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publishDate 2011
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spelling iium-64732011-12-07T15:02:30Z http://irep.iium.edu.my/6473/ Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation Hasan , M. A. Reaz, Mamun Bin Ibne Ibrahimy, Muhammad Ibn T Technology (General) Conventional techniques are often unable to achieve the Fetal Electrocardiogram FECG extraction and Rpeak detection in FECG from the abdominal ECG (AECG) in satisfactorily level for Fetal Heart Rate (FHR) monitoring. A new methodology by combining the Artificial Neural Network (ANN) and Correlation approach has been proposed in this paper. Artificial Neural Network is chosen primarily since it is adaptive to the nonlinear and time-varying features of the ECG signal. The supervised multilayer perception (MLP) network has been used because it requires a desired output in order to learn. Similarly, the Correlation method has been chosen as the correlation factor can be used to scale the MECG when subtracting it from the AECG, in order to get the FECG. By combining these two approaches the proposed methodology gives better and efficient result in terms of accuracy for FECG extraction and R-peak detection in the AECG signal due to its above characteristics. The proposed approach involves the FECG extraction from the AECG signal with the accuracy of 100% and R-peak detection performance is 93.75%, even though the overlapping situation of MECG and FECG signal in the AECG signal. Therefore the physician and clinician can make the correct decision for the well-being status of the fetus and mother during the pregnancy period. 2011-10-03 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/6473/1/Fetal_electrocardiogram_extraction_and_R-peak_detection_for_fetal_heart_rate_monitoring_using_artificial_neural_network_and_Correlation.pdf Hasan , M. A. and Reaz, Mamun Bin Ibne and Ibrahimy, Muhammad Ibn (2011) Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation. In: International Joint Conference on Neural Network (IJCNN 2011), 31 July - 5 August 2011, San Jose, California. http://dx.doi.org/10.1109/IJCNN.2011.6033193 doi:10.1109/IJCNN.2011.6033193
spellingShingle T Technology (General)
Hasan , M. A.
Reaz, Mamun Bin Ibne
Ibrahimy, Muhammad Ibn
Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
title Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
title_full Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
title_fullStr Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
title_full_unstemmed Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
title_short Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
title_sort fetal electrocardiogram extraction and r-peak detection for fetal heart rate monitoring using artificial neural network and correlation
topic T Technology (General)
url http://irep.iium.edu.my/6473/
http://irep.iium.edu.my/6473/
http://irep.iium.edu.my/6473/
http://irep.iium.edu.my/6473/1/Fetal_electrocardiogram_extraction_and_R-peak_detection_for_fetal_heart_rate_monitoring_using_artificial_neural_network_and_Correlation.pdf