EEG (Electroencephalogram) as a Bioelectrical Signal Reflecting Brain Activity

EEG (Electroencephalogram) is a bioelectrical signal that reflects brain activity. Its high time-varying sensitivity makes it particularly vulnerable to external interference during signal acquisition. Physiological activities including eye movements, blinking, electrocardiogram (ECG), and electromyogram (EMG) can introduce noise (artifacts) into authentic EEG signals. These artifacts present substantial challenges for EEG signal analysis and processing. To address this issue, researchers have developed various methodologies spanning from artifact removal techniques in EEG signals to effectiveness evaluation of noise elimination. In this paper, we propose a MATLAB-based implementation employing signal processing algorithms to subtract multiple types of EEG artifacts. The methodology involves implementing digital filters and statistical techniques to isolate and remove artifacts while preserving genuine neural activity patterns through appropriate thresholding and signal decomposition approaches.