A physiological performance metric to assess driving capacity

Driving is a complex task and following a stroke/brain injury it is often up to a clinician e.g., consultant in rehabilitation medicine to decide if the individual can safely return to driving. Currently, these decisions tend to be made based on results gathered from paper-based, psychometric or on-road assessments. The findings from recent literature reveal that there is much controversy remaining around the most appropriate method of determining when it is safe to return to the road following brain injury.

The goal of this proposal is to extend a study currently underway at Ulster which aims to investigate the performance of drivers using a virtual car simulator under various scenarios. The experiment provides data to complement existing studies and assist in deciding if patients with brain injury could be allowed to return to driving. Various measurements will be made to assess the drivers including: brainwaves, eye movement, heart rate, and stress response. These data will then be analysed to produce a model of what a good driver looks like and then used as a baseline to help assess patients with brain injury. The datasets produced will be analysed using various state-of-the-art AI techniques and the system has the potential not only to make it easier to evaluate patients who wish to return to driving but also could allow a more systematic approach to how healthy drivers are assessed before obtaining their driving licence.