An Electrocardiogram (ECG) Plays An Important Role In The Diagnosis Process And Providing Information Regarding Heart Diseases, Monitoring ECG Signal Has High Clinical Significance. Out Of 125 Babies, 1 Baby Born With Some Form Of Congenital Heart Defect Every Year. So Analysis And Synthesis Of Fetal Electrocardiograms (FECG) For Disease Detection Is Very Important. The FECG Is Always Contaminated By Mother’s ECG (MECG) So, Extracting The Clean FECG Signal Is Very Necessary For Fetal Health Monitoring. Currently, There Is An Intense Research Into Noninvasive Methods For Detecting The Fetus At Risk Of Damage Or Death In The Uterus. The Fetal Electrocardiogram (FECG) Provides Useful Information About The Fetus’s Condition. However, ICA Is Computationally Demanding Due To Its Use Of Higher-order Statistics, And Hence, It Is Not Well Suited For Implementation In Real-time Applications. To Cope With This Problem, Traditional Approaches Have Been Based On Adaptive Algorithms Or, More Recently, On The Use Of A Priori Information On The ECG Signal.
