Window Functions Analysis in Filters for EEG Movement Intention Signals

Abstract

The aim of this work is to compare the different windows performance in EEG signals related to movement intention, to find the adequate window in specific frequency bands filters. For this purpose, FIR filters using different window functions were implemented in two kinds of signals: a set of simulated signals and a dataset containing EEG movement intention records taken of PhysioNet. The movement intention could be understood as the product of the neuronal synchronization before the movement onset. The similarity of the results was measured using the Euclidean distance. The results obtained suggest the existence of a window function as the most suitable and robust for the EEG movement intention analysis.