Cross-Day Data Diversity Improves Inter-Individual Emotion Commonality of Spatio-Spectral EEG Signatures Using Independent Component Analysis

• Published in: IEEE transactions on affective computing Vol. 15; no. 1; pp. 1 - 15
• Main Authors: Shen, Yi-Wei, Lin, Yuan-Pin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Affective brain-computer interface (aBCI); Arousal; Brain modeling; Commonality; data diversity; electroencephalogram (EEG); Electroencephalography; Emotional factors; Emotional responses; Emotions; Human-computer interface; Independent component analysis; Integrated circuits; Modulation; multiple-day independent component analysis (ICA); Signatures; Task analysis; Variability

Electroencephalogram (EEG) variability poses a great challenge to the affective brain-computer interface (aBCI) for practical applications. Most aBCI frameworks have been demonstrated successfully but deliberated on single-day data, which can be realistically susceptible to psychophysiological chang...