摘要：Generic emotion prediction models based on physiological data developed in the feld of afective computing apparently are not robust enough . To improve their efectiveness, one needs to personalize them to specifc individuals and incorporate broader contextual information . To address the lack of relevant datasets, we propose the 2nd Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems (BIRAFFE2) dataset . In addition to the classical procedure in the stimulus-appraisal paradigm, it also contains data from an afective gaming session in which a range of contextual data was collected from the game environment . This is complemented by accelerometer, ECG and EDA signals, participants’ facial expression data, together with personality and game engagement questionnaires . The dataset was collected on 102 participants . Its potential usefulness is presented by validating the correctness of the contextual data and indicating the relationships between personality and participants’ emotions and between personality and physiological signals .
