Interactive EEG Emotion Recognition with Incremental Gaussian Processes.

Interactivity is crucial for enabling models to adjust and optimize based on user feedback, thereby enhancing overall performance. However, existing electroencephalogram (EEG)-based emotion recognition models rely on static training paradigms, lack interactivity, and struggle to effectively handle uncertainty in predictions. To address this issue, we propose a novel paradigm for interactive emotion recognition based on incremental Gaussian processes (GP).