Toward the Construction of Affective Brain-Computer Interface: A Systematic Review

Abstract

Electroencephalogram(EEG)-based affective computing aims to recognize the emotional state, which is the core technology of affective brain-computer interface(aBCI). This concept encompasses aspects of physiological computing, human-computer interaction(HCI), mental health care, and brain-computer interfaces(BCI), presenting significant theoretical and practical value. However, the field reached a bottleneck stage due to EEG individual difference issues, causing various challenges to achieve a fundamental aBCI. In this review, we collected some representative works from 2019 to 2023. Combining the historical exploration process and research approaches of EEG-based emotion recognition, a comprehensive understand of current research status was conducted. Furthermore, we analyzed the main obstacles for emotion recognition modeling. To construct a reasonable aBCI, we envisioned the working scenarios, developmental stages, and key impact factors based on the existing EEG physiology knowledge. From the practical application perspective, we evaluated the theoretical significance, implementation difficulty, and real-world limitations of different approaches. By synthesizing the merits and drawbacks of various techniques, we proposed a theoretically feasible aBCI framework under the restrictions of real-world application scenarios. Finally, we suggested several research topics that have not been thoroughly investigated to broaden the research scope and accelerate the development of aBCIs.