Introducing RELAX: An automated pre-processing pipeline for cleaning EEG data - Part 1: Algorithm and application to oscillations

N. W. Bailey, M. Biabani, A. T. Hill, A. Miljevic, N. C. Rogasch, B. McQueen, O. W. Murphy, P. B. Fitzgerald

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)


Objective: Electroencephalographic (EEG) data are often contaminated with non-neural artifacts which can confound experimental results. Current artifact cleaning approaches often require costly manual input. Our aim was to provide a fully automated EEG cleaning pipeline that addresses all artifact types and improves measurement of EEG outcomes Methods: We developed RELAX (the Reduction of Electroencephalographic Artifacts). RELAX cleans continuous data using Multi-channel Wiener filtering [MWF] and/or wavelet enhanced independent component analysis [wICA] applied to artifacts identified by ICLabel [wICA_ICLabel]). Several versions of RELAX were compared using three datasets (N = 213, 60 and 23 respectively) against six commonly used pipelines across a range of artifact cleaning metrics, including measures of remaining blink and muscle activity, and the variance explained by experimental manipulations after cleaning. Results: RELAX with MWF and wICA_ICLabel showed amongst the best performance at cleaning blink and muscle artifacts while preserving neural signal. RELAX with wICA_ICLabel only may perform better at differentiating alpha oscillations between working memory conditions. Conclusions: RELAX provides automated, objective and high-performing EEG cleaning, is easy to use, and freely available on GitHub. Significance: We recommend RELAX for data cleaning across EEG studies to reduce artifact confounds, improve outcome measurement and improve inter-study consistency.

Original languageEnglish
Pages (from-to)178-201
Number of pages24
JournalClinical Neurophysiology
Publication statusPublished - May 2023


  • Artifact reduction
  • Blinks
  • Electroencephalography
  • Muscle
  • Neural oscillations
  • Pre-processing

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