A Novel Technique for Extraction Foetal Electrocardiogram using Adaptive Filtering and Simple Genetic Algorithm
Mahmoud Ahmed Suliman Ali and XiaoPing Zeng
DOI : 10.3844/amjbsp.2010.75.81
Current Research in Biostatistics
Volume 1, Issue 2
Problem statement: Foetal electrocardiogram (FECG) was the best method used to diagnose Foetal heart problem. Knowledge of the foetal heart signal prevents Foetal problems in the earlier stage. Recently, there has been a growing interest in noninvasive method rather than the old invasive method which was more risky for the mother's health. The most significant problem in noninvasive method is the extraction of the Foetal signals from maternal signals and many contaminated noises. The problems of extraction of the Foetal signals are the problems that plagued researchers in the field of signal processing. Objective to develop a technique for extracting FECG signals based on adaptive filter and simple Genetic algorithm. Approach: Practical method for extraction using computer simulations was proposed. The proposed method detects Foetal ECG by denoising abdominal ECG (AECG) and lead to the subsequent cancellation of maternal ECG (MECG) by adaptive filtering. The thoracic signal (TECG) which is purely of Mother signal (MECG) was used to cancel MECG in abdominal signal and the Foetal ECG detector extracts the FECG through Simple Genetic algorithm which enters as the editor of unwanted noise. Results: The FECG signal which was obtained appears to agree with the standard Foetal ECG signals. A program for carrying out the calculations was developed in matlab. The testing of the algorithms was done by using real data from SISTA/DAISY and Physionet. Conclusion: The proposed technique for extraction of FECG was useful and the results appear to agree with the mean values of FECG.
© 2010 Mahmoud Ahmed Suliman Ali and XiaoPing Zeng. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.