The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects

Sensors (Basel). 2021 Nov 19;21(22):7711. doi: 10.3390/s21227711.

Abstract

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.

Keywords: ERP; filters; preprocessing data; somatosensory cortex.

MeSH terms

  • Algorithms
  • Artifacts
  • Blinking
  • Electroencephalography
  • Healthy Volunteers
  • Humans
  • Motor Cortex*
  • Signal Processing, Computer-Assisted