Temporal Response Comparison Following Digital Filter Application on EEG Signals

This study focused on analyzing the response of electroencephalographic (EEG) signals to the application of different digital filters. EEG signals (14 electrodes) were recorded at rest, with no external stimuli present. The EEG recordings were subdivided into four sub-bands: Delta, Theta, Alpha, and Beta. The analysis was performed in the time domain, focusing on signal amplitude, frequency, and morphology.The EEG signals were represented through their frequency distribution and modeled as curves with a normal probability distribution. Convolution operations were performed between pairs of digital filters over these distributions to identify which filters exhibited lower temporal variability.The results of the comparative analysis revealed that the filters induced variable responses. In the Delta band, the sym9 filter showed greater selectivity and stronger presence across electrodes. For the Theta band, the db1 filter presented the lowest variability across all electrodes. In the Alpha and Beta bands, the db2 filter showed both lower variability and stronger signal presence.This study demonstrates that the response of EEG signals to different digital filters can lead to variations in the resulting signal characteristics. Although the differences are subtle, taking them into account could contribute to more objective results in EEG signal processing.