Dealing with eye artifacts in EEG preprocessing: Comparing Artifact Rejection and Correction Methods

Autor: Gref, Daria, Rahman, Rasha Abdel, Enge, Alexander
Rok vydání: 2023
Předmět:
DOI: 10.17605/osf.io/frw4k
Popis: This study aims to compare different techniques for reducing the impact of eye artifacts on electroencephalography (EEG) data. Four pipelines will be created, each representing a different approach, and applied to pre-recorded EEG data from 40 participants. The pipelines will be evaluated by comparing the data quality after pre-processing using standardized measurement errors.
Databáze: OpenAIRE