Abstract
The extraction of a fetal electrocardiogram (FECG) is critical in medical diagnostics for monitoring the fetus’s physiological status during pregnancy. The ECG can be used to detect a variety of heart-related disorders. A QRS complex, P wave, and T wave make up an ECG signal during a cardiac cycle. The identification of R peaks in an abdominal CT scan, which are the peaks of the QRS complex. Adaptive filters are utilized to abstract FECG from a combination of maternal electrocardiogram (MECG) and FECG. An effective method primarily used by hospitals to investigate fetal health status during the first trimester is deriving FECG from a pregnant woman’s non-invasively recorded abdominal ECG signal. This ECG of the abdomen contains maternal and fetal ECGs (MECG+FECG), as well as interference and other noises. We proposed employing adaptive filters to eliminate background artifacts and noise from FECG signals in this work. For FECG extraction, the suggested approach employs adaptive noise cancellation. The fetal heart rate can be resulting by measuring the peaks of the R-R interval using the threshold value from the extracted FECG, according to the results, which are noise-free signals. This work presents a comprehensive model for extracting FECG and determining the heart rate of FECG signals, which aids in the classification of abnormal and normal classes. The obtained result demonstrates that the proposed technique is powerful in calculating FECG and has the potential to improve the accuracy and usability of abdominal electrocardiography technologies in the future.
Published Version
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