EEG artifact removal—state-of-the-art and guidelines

By Jose Antonio Urigüen, Begonya García-Zapirain Soto. Journal of Neural Engineering, 2015

883 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Signal Processing

View Paper: https://www.semanticscholar.org/paper/0b57857195c1798b9580f7911f6d1ed407bb135d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Manuel José Fonseca
2. Guibin Bian
3. Zean Tian
4. Xiao Jiang
5. Soraia M. Alarcão

In Signal Processing

1. Manuel José Fonseca
2. Guibin Bian
3. Zean Tian
4. Xiao Jiang
5. Soraia M. Alarcão

Citations in the corpus

• Emotions Recognition Using EEG Signals: A Survey (2019, background): “For further information about EEG artifact removal, please see [132].”
• Removal of Artifacts from EEG Signals: A Review (2019, methodology): “[21].”
• Reliable but Wrong? Automated Detection of Heart Rate Artifacts as a Source of Bias in Pediatric EEG Data (2026, unknown): “Artifacts can occur due to technical problems such as faulty EEG nets, behavioral problems such as movement of the participant, physiological factors (i.e., eye blinks, eye movement, heart rate), and environmental noise, all of which are not of interest to most researchers [1, 2].”