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

Aleksandra Kawala-Sterniuk,Monika Blaszczyszyn,Edward Jacek Gorzelanczyk,Stepan Ozana,Radek Martinek,Mariusz Pelc,Michal Podpora

doi:10.3390/s20030807

Abstract

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.

Highlights

The human brain is one of the most important organs, which is responsible for electrical signals’transmission all over the body and is mainly controlled by the nervous system
The authors of this paper focus mainly on electroencephalography as a non-invasive method of brain activity measurement and the obtained data is very useful to diagnose and to monitor various disorders such as inter alia head trauma, tumors, epilepsy, sleep problems [17,18,19]
The data was recorded with the implementation of 64 Ag/AgCl active electrodes placed in accordance with the 10-10 system

Summary

Introduction

The human brain is one of the most important organs, which is responsible for electrical signals’transmission all over the body and is mainly controlled by the nervous system. The human brain is one of the most important organs, which is responsible for electrical signals’. The brain-generated electrical data is known as electroencephalograph (EEG) [1,2]. Analysis of biomedical data has been the subject of analysis for numerous researchers all over the world, despite its challenging nature. This is because they are frequently riddled with various internal and external artifacts such as high-frequency noise, or in case of EEG, by another biomedical signal such as electromyography (EMG), electrocardiography (ECG) or electrooculography (EOG) [3,4,5,6]. Electroencephalography provides manifold useful information regarding inter alia various psychological dysfunctions or mental illnesses and even hints on how the mind works [9,10]

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Conclusion