Karpiel Ilona, Kurasz Zofia, Kurasz Rafał, Duch Klaudia
Łukasiewicz Research Network-Institute of Medical Technology and Equipment, 41-800 Zabrze, Poland.
Institute of Psychology, University of Silesia, 40-007 Katowice, Poland.
Sensors (Basel). 2021 Nov 19;21(22):7711. doi: 10.3390/s21227711.
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.
原始脑电图（EEG）信号总是受到许多不同伪迹的污染，例如肌肉运动（肌电图伪迹）、眨眼（眼电图伪迹）或电力线干扰。为了正确解读数据，必须去除所有伪迹。然而，各种降噪方法会显著影响EEG信号的最终形态，进而影响其特征值、潜伏期和幅度。在EEG数据处理的早期阶段，有几种类型的滤波器可用于消除噪声。然而，对于它们的使用并没有金标准。本文旨在验证和比较四种不同滤波器（有限脉冲响应滤波器（FIR）、无限脉冲响应滤波器（IIR）、快速傅里叶变换滤波器（FFT）、陷波滤波器（NOTCH））对EEG信号潜伏期和幅度的影响。通过对选定滤波器进行比较，作者旨在提高研究人员对已知滤波器在选定区域——感觉运动区对潜伏期和幅度影响的认识。
