Assessing Dynamic Flow Experience from EEG Signals: A Processing-based Approach

As an interaction experience goal, the flow experience is characterized by its subjectivity and dynamism.Exploring objective methods to assess dynamic flow states is significant in enhancing user experience design, evaluation, and optimization.This study aims to model the dynamics of the flow experience and quantify its intensity using electroencephalography signals (EEG) from the perspective of the process.To achieve this, an interactive task is designed to induce dynamic changes in flow, and EEG signals from participants were recorded simultaneously, to form a flow assessment dataset.Subsequently, a frequency-aware convolutional Transformer model