Custom Domain Adaptation: A New Method for Cross-Subject, EEG-Based Cognitive Load Recognition

• Published in: IEEE signal processing letters Vol. 27; pp. 750 - 754
• Main Authors: Jimenez-Guarneros, Magdiel, Gomez-Gil, Pilar
• Format: Journal Article
• Language: English
• Published: New York IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation; Artificial neural networks; cognitive load; Cognitive tasks; Computer vision; Deep learning; Domains; EEG-based classification; Electroencephalography; Machine learning; Neural networks; Task analysis; Testing; Training; Unsupervised domain adaptation

Electroencephalograms (EEG) have shown to be a useful approach to measure the cognitive load in tasks where mental effort is involved. However, EEG signals present a high variability among subjects as well as a non-stationary behavior, so that distributions among samples of different subjects are mi...