Extraction of Fetal ECG Using ANFIS and the Undecimated-Wavelet Transform

A trans-thoracic interpretation of the electrical activity of the heart throughout time collected and externally recorded by skin electrodes is electrocardiograph. An electrocardiographic device creates this recording, and it does not involve any invasive procedures. This research focuses on the extraction of fetal ECG from the maternal ECG using adaptive neuro fuzzy inference system (ANFIS) and undecimated wavelet transform (UWT), which combines the desirable qualities of ANFIS and UWT. The objective of this paper is to improve the accuracy of fetal ECG analysis. In a lot of applications, the network needs to imitate non-linear and time-varying functions, which means that the functions could change based on the incoming signal and other parameter alterations. This is necessary since non-linear functions are more complex than linear functions. In situations like these, a greater number of signals may be reproduced at random, and the approaches that are used were evaluated for their ability to accurately determine the fetal ECG as well as for their potential use in other diagnostic applications. This hybrid network was able to quickly tackle the difficult problem, making it superior to conventional adaptive approaches.