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Analyzing the Impact of Cognitive Load in Evaluating Gaze-based Typing
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.Comment: 6 pages, 4 figures, IEEE CBMS 201
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