An Efficient Method for Fetal Electrocardiogram Extraction from the Abdominal Electrocardiogram Signal

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.

Fetal Electrocardiogram Extraction Based on SWT-MM Method

“…For instance, the ST waveform of the FECG suggests the ability of fetal heart muscle to respond to the stress of labor [2]. Also the extraction of the QRS complex, particularly detection of the R-peak, provides the information for a study of the heart rate variability [3]. Since the FECG detected directly from maternal abdomen surface is rather weak and approximately masked by other signals, to extract the FECG is facing lots of difficulties.…”

Bio-Potential Signal Extraction from Multi-Channel Paper Recorded Charts

“…In this study, a method for bio-potential signal extraction from single or multi-channel paper recorded charts using image processing techniques is developed (Gonzalez and Woods, 2002;Ali and Zeng, 2010;AlMejrad, 2010b;Kumar et al, 2009;Hasan et al, 2009). After scanning the study charts and converting them into images using a commercial scanner, an algorithm is applied to eliminate the background of the scanned paper chart from any recording device single channel or multi-channel using binary neighborhood morphological operations then converting the extracted waveform image into quantized values representing the waveform recorded paper chart.…”