Analyzing the Impact of Cognitive Load in Evaluating Gaze-based Typing
This work addresses the need for better usability assessment in gaze-based typing interfaces for users with motor impairments or in specialized environments, though it is incremental by adding cognitive metrics to existing evaluation frameworks.
The study tackled the problem of evaluating gaze-based virtual keyboards by arguing for including cognitive load as a measure, finding that while conventional metrics showed no significant differences between three keyboard designs, EEG analysis revealed variances in mental workload and cognition during typing phases.
Gaze-based virtual keyboards provide an effective interface for text entry by eye movements. The efficiency and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystrokes per character, backspace usage, etc. However, in comparison to the traditional text entry approaches, gaze-based typing involves natural eye movements that are highly correlated with human brain cognition. Employing eye gaze as an input could lead to excessive mental demand, and in this work we argue the need to include cognitive load as an eye typing evaluation measure. We evaluate three variations of gaze-based virtual keyboards, which implement variable designs in terms of word suggestion positioning. The conventional text entry metrics indicate no significant difference in the performance of the different keyboard designs. However, STFT (Short-time Fourier Transform) based analysis of EEG signals indicate variances in the mental workload of participants while interacting with these designs. Moreover, the EEG analysis provides insights into the user's cognition variation for different typing phases and intervals, which should be considered in order to improve eye typing usability.