Extraction and noise reduction of the fetal electrocardiogram using Savitzky-Golay and adaptive filters

Today, cardiovascular disease is one of the most significant threats to fetuses. The electrocardiogram (ECG) is a common, low-cost way to detect arrhythmias that might cause sudden death. A large number of babies are born with a heart abnormality, which leads to birth defect-related fatalities. Many techniques have been presented for a better ECG signal with low noise. Many resources impair recorded signals because of the tiny amplitude of cardiac impulses, which are only a few millivolts. As a result, they can’t help with illness diagnosis. When the patient is physically involved, the negative repercussions are exacerbated. The objective of this research is to find effective ways to remove anomalies in the embryonic cardiac signal. A strategy for minimizing noise is presented in this paper. To enhance the fetal cardiac signal obtained from the mother, an active noise cancellation (ANC) machine was employed in this case (FENC system). Adaptive LMS and normalized LMS are among the algorithms used. Combining the recommended ANC with an (SG) filter improves the FENC system. Findings demonstrate that the suggested FENC is more accurate and suitable than prior approaches.