Development and Validation of Pictographic Scales for Rapid Assessment of Affective States in Virtual Reality

摘要

This paper describes the development and validation of a continuous pictographic scale for self-reported assessment of affective states in virtual environments. The developed tool, called Morph A Mood (MAM), consists of a 3D character whose facial expression can be adjusted with simple controller gestures according to the perceived affective state to capture valence and arousal scores. It was tested against the questionnaires Pick-A-Mood (PAM) and Self-Assessment Manikin (SAM) in an experiment in which the participants (N = 32) watched several one-minute excerpts from music videos of the DEAP database within a virtual environment and assessed their mood after each clip. The experiment showed a high correlation with regard to valence, but only a moderate one with regard to arousal. No statistically significant differences were found between the SAM ratings of this experiment and MAM, but between the valence values of MAM and the DEAP database and between the arousal values of MAM and PAM. In terms of user experience, MAM and PAM hardly differ. Furthermore, the experiment showed that assessments inside virtual environments are significantly faster than with paper-pencil methods, where media devices such as headphones and display goggles must be put on and taken off.