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EEG Artifact Removal Techniques by Houichette Amira is a document available to read on EtoBox.

This document evaluates the effectiveness of Artifact Subspace Reconstruction (ASR) for automatic EEG artifact removal, particularly in real EEG data from a simulated driving experiment. The study finds that ASR can effectively remove transient and large-amplitude artifacts while preserving brain signals, with optimal cutoff parameters ranging from 10 to 100. The results indicate that ASR can be a powerful tool for both offline data analysis and online EEG applications, such as clinical monitoring and brain

Author
Houichette Amira
Language
EN