The Effects of Filter's Class, Cutoff Frequencies, and Independent Component Analysis on the Amplitude of Somatosensory Evoked Potentials Recorded from Healthy Volunteers

Muhammad Samran Navid, Imran Khan Niazi, Dina Lelic, Asbjørn Mohr Drewes, Heidi Haavik

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

OBJECTIVE: The aim of this study was to investigate the effects of different preprocessing parameters on the amplitude of median nerve somatosensory evoked potentials (SEPs).

METHODS: Different combinations of two classes of filters (Finite Impulse Response (FIR) and Infinite Impulse Response (IIR)), three cutoff frequency bands (0.5-1000 Hz, 3-1000 Hz, and 30-1000 Hz), and independent component analysis (ICA) were used to preprocess SEPs recorded from 17 healthy volunteers who participated in two sessions of 1000 stimulations of the right median nerve. N30 amplitude was calculated from frontally placed electrode (F3).

RESULTS: The epochs classified as artifacts from SEPs filtered with FIR compared to those filtered with IIR were 1% more using automatic and 140% more using semi-automatic methods (both p < 0.001). There were no differences in N30 amplitudes between FIR and IIR filtered SEPs. The N30 amplitude was significantly lower for SEPs filtered with 30-1000 Hz compared to the bandpass frequencies 0.5-1000 Hz and 3-1000 Hz. The N30 amplitude was significantly reduced when SEPs were cleaned with ICA compared to the SEPs from which non-brain components were not removed using ICA.

CONCLUSION: This study suggests that the preprocessing of SEPs should be done carefully and the neuroscience community should come to a consensus regarding SEP preprocessing guidelines, as the preprocessing parameters can affect the outcomes that may influence the interpretations of results, replicability, and comparison of different studies.

Original languageEnglish
Article number2610
JournalSensors (Basel, Switzerland)
Volume19
Issue number11
Number of pages18
ISSN1424-8220
DOIs
Publication statusPublished - 8 Jun 2019

Keywords

  • EEG
  • ICA
  • SEPs
  • filtering
  • preprocessing

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