This paper covers a brief review of both the advantages and disadvantages of the implementation of various smoothing filters in the analysis of electroencephalography (EEG) data for the purpose of potential medical diagnostics. The EEG data are very prone to the occurrence of various internal and external artifacts and signal distortions. In this paper, three types of smoothing filters were compared: smooth filter, median filter and Savitzky-Golay filter. The authors of this paper compared those filters and proved their usefulness, as they made the analyzed data more legible for diagnostic purposes. The obtained results were promising, however, the studies on finding perfect filtering methods are still in progress.

Nicolaus Copernicus University Collegium Medicum Department of Theoretical Basis of BioMedical Sciences and Medical Informatics 85 067 Bydgoszcz Poland Kazimierz Wielki University Institute of Philosophy 85 092 Bydgoszcz Poland Babinski Specialist Psychiatric Healthcare Center Outpatient Addiction Treatment 91 229 Lodz Poland The Society for the Substitution Treatment of Addiction Medically Assisted Recovery 85 791 Bydgoszcz Poland

Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45 758 Opole Poland

Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45 758 Opole Poland University of Greenwich Department of Computing and Information Systems SE10 9LS London UK

Opole University of Technology Faculty of Physical Education and Physiotherapy 45 758 Opole Poland

VSB Technical University Ostrava FEECS Department of Cybernetics and Biomedical Engineering Ostrava Poruba 708 00 Czech Republic

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