An Overview of ECG Artifact Detection in EEG Signals

Abstract Electroencephalography (EEG) is an important technique for recording brain signals and is particularly used in the diagnosis and treatment of neurological diseases such as epilepsy. However, due to the complex nature of EEG signals, their interpretation is difficult and time-consuming. In EEG recordings, physiological noises such as eye movements (EOG) and electrocardiography (ECG) can affect the signals and hinder accurate diagnosis. This study emphasizes the importance of removing noise from EEG signals, with a focus on the impact of ECG-induced noise. The detection of QRS complexes in the ECG signal plays a critical role in eliminating these noise components from EEG signals. The QRS-complex, a prominent marker of the heart's electrical activity, helps in removing the corresponding noise components from EEG signals. As a result, removing noise from EEG signals is crucial for accurate diagnosis, and it is believed that future studies in this area could develop more precise methods.