Real-time estimation of EEG-based engagement in different tasks.
Angela NatalizioSebastian SieghartsleitnerLeonhard SchreinerMartin WalchshoferAntonio EspositoJosef ScharingerHarald PretlPasquale ArpaiaMarco ParvisJordi Sole-CasalsMarc Sebastián-RomagosaRupert OrtnerChristoph GugerPublished in: Journal of neural engineering (2024)
= 0.44, p < 0.001). Finally, theta and alpha band powers were investigated, which respectively increased and decreased during more engaging states.
Significance: This study proposes a task-specific EEG engagement estimation model with cross-task capabilities, offering a framework for real-world applications.