Related Experiment Video
Updated: Aug 9, 2025
06:40
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
10.2K
Introducing RELAX: An automated pre-processing pipeline for cleaning EEG data - Part 1: Algorithm and application to
N W Bailey1, M Biabani2, A T Hill3
1Central Clinical School Department of Psychiatry, Monash University, Camberwell, Victoria, Australia; School of Medicine and Psychology, The Australian National University, Canberra, ACT, Australia; Monarch Research Institute Monarch Mental Health Group, Sydney, NSW, Australia.
Summary
RELAX, a new automated pipeline, effectively cleans electroencephalographic (EEG) data by removing artifacts. This tool enhances measurement accuracy and consistency in EEG studies.
Area of Science:
- Neuroscience
- Signal Processing
Background:
- Electroencephalographic (EEG) data frequently contain non-neural artifacts.
- Manual artifact cleaning is time-consuming and costly.
- Automated solutions are needed to improve EEG data quality.
Purpose of the Study:
- To develop a fully automated EEG cleaning pipeline, named RELAX (Reduction of Electroencephalographic Artifacts).
- To address all major artifact types in EEG data.
- To improve the measurement of EEG outcomes.
Main Methods:
- RELAX utilizes Multi-channel Wiener filtering (MWF) and/or wavelet enhanced independent component analysis (wICA).
- Artifacts are identified using ICLabel for wICA (wICA_ICLabel).
- Performance was evaluated on three datasets against six existing pipelines using various artifact cleaning metrics.
Main Results:
- RELAX, particularly with MWF and wICA_ICLabel, demonstrated superior performance in removing blink and muscle artifacts while preserving neural signals.
- The wICA_ICLabel-only version showed potential for better differentiation of alpha oscillations in cognitive tasks.
- RELAX achieved high performance in artifact reduction and signal preservation.
Conclusions:
- RELAX offers an automated, objective, and high-performing solution for EEG data cleaning.
- The pipeline is user-friendly and publicly available.
- RELAX is recommended for reducing artifact confounds and enhancing inter-study consistency in EEG research.
