Affective brain-computer interface (BCI) is an important direction in the BCI field, primarily divided into two major types: emotion recognition and emotion regulation. The former aims to accurately recognize human emotions, while the latter seeks to achieve personalized emotion regulation based on emotion recognition. This talk will first briefly review the research background and recent advances in affective BCIs, and then systematically introduce the speaker’s team research achievements in the neural mechanisms, fundamental algorithms, EEG foundation models, and public datasets for emotion recognition BCIs. The talk will also present their objective depression assessment system built upon a multimodal affective BCI—the Emotion “X-ray” machine. Finally, the talk will discuss the prospects and challenges in the development of affective BCIs.

Speaker

Prof. Baoliang Lv

School of Computer Science, SJTU

Time

 2026.5.6 12:00-13:30