The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects
The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction me...
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MDPI AG
2021
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oai:doaj.org-article:919a652df96c457893771f64f1211bcd2021-11-25T18:58:42ZThe Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects10.3390/s212277111424-8220https://doaj.org/article/919a652df96c457893771f64f1211bcd2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7711https://doaj.org/toc/1424-8220The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final shape of the EEG signal and thus its characteristic values, latency and amplitude. There are several types of filters to eliminate noise early in the processing of EEG data. However, there is no gold standard for their use. This article aims to verify and compare the influence of four various filters (FIR, IIR, FFT, NOTCH) on the latency and amplitude of the EEG signal. By presenting a comparison of selected filters, the authors intend to raise awareness among researchers as regards the effects of known filters on latency and amplitude in a selected area—the sensorimotor area.Ilona KarpielZofia KuraszRafał KuraszKlaudia DuchMDPI AGarticlepreprocessing datasomatosensory cortexERPfiltersChemical technologyTP1-1185ENSensors, Vol 21, Iss 7711, p 7711 (2021) |
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preprocessing data somatosensory cortex ERP filters Chemical technology TP1-1185 |
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preprocessing data somatosensory cortex ERP filters Chemical technology TP1-1185 Ilona Karpiel Zofia Kurasz Rafał Kurasz Klaudia Duch The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects |
description |
The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final shape of the EEG signal and thus its characteristic values, latency and amplitude. There are several types of filters to eliminate noise early in the processing of EEG data. However, there is no gold standard for their use. This article aims to verify and compare the influence of four various filters (FIR, IIR, FFT, NOTCH) on the latency and amplitude of the EEG signal. By presenting a comparison of selected filters, the authors intend to raise awareness among researchers as regards the effects of known filters on latency and amplitude in a selected area—the sensorimotor area. |
format |
article |
author |
Ilona Karpiel Zofia Kurasz Rafał Kurasz Klaudia Duch |
author_facet |
Ilona Karpiel Zofia Kurasz Rafał Kurasz Klaudia Duch |
author_sort |
Ilona Karpiel |
title |
The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects |
title_short |
The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects |
title_full |
The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects |
title_fullStr |
The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects |
title_full_unstemmed |
The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects |
title_sort |
influence of filters on eeg-erp testing: analysis of motor cortex in healthy subjects |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/919a652df96c457893771f64f1211bcd |
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