Key result
The study compared the influence of FIR, IIR, FFT, and NOTCH filters on the latency and amplitude of the EEG signal in the sensorimotor area, though quantitative results were not reported.
Why the study?
Noise reduction methods significantly influence EEG signal latency and amplitude, but no gold standard exists for filter use in processing EEG data.
This study highlights the impact of different noise reduction filters on the latency and amplitude of EEG signals in the sensorimotor area.
EEG artifact filters alter signal latency/amplitude; leaves open optimal methods for reliable clinical and research use.
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.
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Karpiel et al. (2021) studied Healthy Subjects. EEG filters (FIR, IIR, FFT, NOTCH) was evaluated on Latency and amplitude of the EEG signal. The study compared the influence of FIR, IIR, FFT, and NOTCH filters on the latency and amplitude of the EEG signal in the sensorimotor area, though quantitative results were not reported.
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