Predicting Users’ Difficulty Perception in Virtual Reality Games

Description

  • George Mason University

  • 01.01.2024

Proposed an application that predicts users’ perception of difficulty in a VR game by collecting data, and using a pretrained machine learning model to form personalized predictions over all levels.
Obtained IRB certificate, collected gameplay, user, and medical data through 70+ user studies. Trained a recurrent neural network to understand relationships between collected user data, gameplay data, and game parameters.