We report an experiment (N=18) where participants where engaged in a dual task setting in a Social VR (Virtual Reality) scenario. We present a physiologically-adaptive system that optimizes the virtual environment based on physiological arousal, i.e., electrodermal activity. We investigated the usability of the adaptive system in a simulated social virtual reality scenario. Participants completed an n-back task (primary) and a visual detection (secondary) task. Here, we adapted the visual complexity of the secondary task in the form of the number of not-playable characters of the secondary task to accomplish the primary task. We show that an adaptive virtual reality can improve users’ comfort by adapting to physiological arousal the task complexity.

Specifically we make available physiological (Electrodermal Activity - EDA, Electroencephalography - EEG; Electrocardiography - ECG) , behavioral and questionnaires data and lastly, the analysis code.

Users interested in reproducing the results can follow the methodology as reported in the paper and the analysis code as reported in the Python script (" Step_02.") in the Files section.