@article {10.3844/jcssp.2009.619.623,
article_type = {journal},
title = {An Efficient Method for Fetal Electrocardiogram Extraction from the Abdominal Electrocardiogram Signal},
author = {Hasan, Muhammad Asraful and Ibrahimy, Muhammad Ibn and Reaz, Mamun Bin Ibn},
volume = {5},
number = {9},
year = {2009},
month = {Sep},
pages = {619-623},
doi = {10.3844/jcssp.2009.619.623},
url = {https://thescipub.com/abstract/jcssp.2009.619.623},
abstract = {Problem statement: FECG (Fetal Electrocardiogram) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during pregnancy and labor. Approach: Conventional techniques were often unable to achieve the extraction of FECG from the Abdominal ECG (AECG) in satisfactorily level. A new methodology by combining the Artificial Neural Network (ANN) and Correlation (ANNC) approach had been proposed in this study. Results: The accuracy of the proposed method for FECG extraction from the AECG signal was about 100% and the performance of the method for FHR extraction is 93.75%. Conclusions/Recommendations: The proposed approach involved the FECG extraction even though the MECG and FECG are overlapped in the AECG signal so that the physician and clinician can make the correct decision for the well-being of the fetus and mother during the pregnancy period.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}