Physiological-Based Difficulty Assessment for Virtual Reality Rehabilitation Games

This paper proposes an empirical framework that aims to classify difficulty according to the player's physiological response. As part of the experimental protocol, a simple puzzle-based Virtual Reality (VR) videogame with three levels of difficulty was developed, each targeting a distinct region of the valence-arousal space. A study involving 32 participants was conducted, during which physiological responses (EDA, ECG, Respiration), were measured alongside emotional ratings, which were self-assessed using the Self-Assessment Manikin (SAM) during gameplay. Statistical analysis of the self-reports verified the effectiveness of the three levels in eliciting different emotions. Furthermore, classification using a Support Vector Machine (SVM) was performed to predict difficulty considering the physiological responses associated with each level. Results report an overall F1-score of 74.05% in detecting the three levels of difficulty, which validates the adopted methodology and encourages further research with a larger dataset.