A brain-computer interface (BCI) enables a user to communicate directly with a computer using only the central nervous system. An affective BCI (aBCI) monitors and/or regulates the emotional state of the brain, which could facilitate human cognition, communication, decision-making, and health. This talk introduces first the basic concepts of BCIs, and then in detail the individual components in a closed-loop aBCI system, including signal acquisition, signal processing, feature extraction, emotion recognition, and brain stimulation. Next, it describes three representative applications of aBCIs, i.e., cognitive workload recognition, fatigue estimation, and depression diagnosis and treatment. Several challenges and opportunities in aBCI research and applications, including brain signal acquisition, emotion labeling, diversity and size of aBCI datasets, algorithm comparison, negative transfer in emotion recognition, and privacy protection and security of aBCIs, are also explained.

Reference 

Wu, D., Lu, B. L., Hu, B., & Zeng, Z. (2023). Affective Brain-Computer Interfaces (aBCIs): A Tutorial. Proceedings of the IEEE, 111(10), 1314-1332. https://doi.org/10.1109/JPROC.2023.3277471