ECG Signal Dataset for Fetal ECG Separation

Many researchers working on fetal ECG separation face a significant challenge: the lack of suitable ECG data. To address this issue, I have uploaded an ideal ECG signal dataset collected through electrodes placed on the maternal chest and abdomen. This dataset serves as a valuable resource for both research and practical applications in fetal ECG separation. When processing this data, researchers can implement algorithms like independent component analysis (ICA) or adaptive filtering to isolate fetal cardiac components. By analyzing these ECG signals, we can gain deeper insights into fetal heart activity patterns and better monitor fetal health conditions. The dataset structure supports direct import into MATLAB or Python environments, with typical preprocessing steps including baseline wander removal and notch filtering for powerline interference. This uploaded ECG signal holds substantial importance for advancing research and applications in the field of fetal ECG separation.