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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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-11, Vol.21 (22), p.7711
Main Authors: Karpiel, Ilona, Kurasz, Zofia, Kurasz, Rafał, Duch, Klaudia
Format: Article
Language:English
Subjects:
Alzheimer's disease
Blinking
Data processing
Electroencephalography
ERP
Experiments
filters
Muscles
Noise reduction
Power lines
preprocessing data
Signal processing
Software
somatosensory cortex
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21227711