Analyzing the Impact of Cognitive Load in Evaluating Gaze-based Typing
Gaze-based virtual keyboards allow people with motor disability a method for text entry by eye movements. The effectiveness and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystroke saving, error rate, accuracy, etc. However, in comparison to the conventional 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 have variable design 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 Transformation) based analysis of EEG signals indicate variances in the mental workload of participants while interacting with these designs. Moreover, the EEG analysis provides us insights into the user’s cognition variation in different typing phases and intervals, which should be considered to improve eye typing usability.
Korok Sengupta's picture
Korok Sengupta
University of Koblenz (DE)
Jun Sun's picture
Jun Sun
Raphael Menges's picture
Raphael Menges
Institute for Web Science and Technologies (DE)
Chandan Kumar's picture
Chandan Kumar
University of Koblenz (DE)
Steffen Staab's picture
Steffen Staab