A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings
Background EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: t...
Main Authors: | Gabriella Tamburro, Patrique Fiedler, David Stone, Jens Haueisen, Silvia Comani |
---|---|
Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2018-02-01
|
Series: | PeerJ |
Subjects: | |
Online Access: | https://peerj.com/articles/4380.pdf |
Similar Items
-
Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications
by: David B. Stone, et al.
Published: (2018-03-01) -
Is Brain Dynamics Preserved in the EEG After Automated Artifact Removal? A Validation of the Fingerprint Method and the Automatic Removal of Cardiac Interference Approach Based on Microstate Analysis
by: Gabriella Tamburro, et al.
Published: (2021-01-01) -
Automatic Removal of Cardiac Interference (ARCI): A New Approach for EEG Data
by: Gabriella Tamburro, et al.
Published: (2019-05-01) -
Electromyogram (EMG) Removal by Adding Sources of EMG (ERASE)—A Novel ICA-Based Algorithm for Removing Myoelectric Artifacts From EEG
by: Yongcheng Li, et al.
Published: (2021-01-01) -
Refinement of High-Gamma EEG Features From TBI Patients With Hemicraniectomy Using an ICA Informed by Simulated Myoelectric Artifacts
by: Yongcheng Li, et al.
Published: (2020-11-01)