Framework for Electroencephalography-based Evaluation of User Experience
This work addresses the need for better usability assessment in complex computer systems, though it is incremental as it builds on existing EEG and interaction methods.
The paper tackled the problem of evaluating user experience by developing a framework that uses EEG to continuously estimate mental workload, attention, and error recognition during interaction tasks, validated in a controlled virtual environment with comparisons between keyboard and touch-based interfaces.
Measuring brain activity with electroencephalography (EEG) is mature enough to assess mental states. Combined with existing methods, such tool can be used to strengthen the understanding of user experience. We contribute a set of methods to estimate continuously the user's mental workload, attention and recognition of interaction errors during different interaction tasks. We validate these measures on a controlled virtual environment and show how they can be used to compare different interaction techniques or devices, by comparing here a keyboard and a touch-based interface. Thanks to such a framework, EEG becomes a promising method to improve the overall usability of complex computer systems.