Datadriven Human Intention Analysis : Supported by Virtual Reality and Eye Tracking

Licentiate thesis, 2021

The ability to determine an upcoming action or what decision a human is about to take, can be useful in multiple areas, for example in manufacturing where humans working with collaborative robots, where knowing the intent of the operator could provide the robot with important information to help it navigate more safely. Another field that could benefit from a system that provides information regarding human intentions is the field of psychological testing where such a system could be used as a platform for new research or be one way to provide information in the diagnostic process. The work presented in this thesis investigates the potential use of virtual reality as a safe, customizable environment to collect gaze and movement data, eye tracking as the non-invasive system input that gives insight into the human mind, and deep machine learning as the tool that analyzes the data. The thesis defines an experimental procedure that can be used to construct a virtual reality based testing system that gathers gaze and movement data, carries out a test study to gather data from human participants, and implements an artificial neural network in order to analyze human behaviour. This is followed by four studies that gives evidence to the decisions that were made in the experimental procedure and shows the potential uses of such a system.