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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10244273" target="_blank" >RIV/61989100:27240/20:10244273 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/1424-8220/20/3/807" target="_blank" >https://www.mdpi.com/1424-8220/20/3/807</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s20030807" target="_blank" >10.3390/s20030807</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000867" target="_blank" >EF16_019/0000867: Centrum výzkumu pokročilých mechatronických systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Sensors (Basel, Switzerland)

ISSN

1424-8220

e-ISSN

—

Svazek periodika

20

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

19

Strana od-do

—

Kód UT WoS článku

000517786200231

EID výsledku v databázi Scopus

2-s2.0-85079052797