Comparison of Smoothing Filters in Analysis of EEG Data for the Medical Diagnostics Purposes

. 2020 Feb 02 ; 20 (3) : . [epub] 20200202

Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid32024267

Grantová podpora
CZ.02.1.01/0.0/0.0/16_019/0000867 European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems Projec

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.

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