Evaluation of Different Onscreen Keyboard Layouts Using EEG Signals

The paper aims at evaluation of different onscreen keyboard layouts based on the biological responses of the users. The signal used for the said purpose is Electroencephalogram acquired by low cost neuro-headset from Emotiv. We propose to use human cognition as the fundamental feature to discriminate between user-friendly vs. cumbersome onscreen layout designs. To validate our observations we compared our results with bench marked data based on user study and KLM-GOMS model. A classifier is first trained for high and low cognition tasks based on well-established cognitive tests (e.g. Stroop test) and then this classifier is used to report the cognition class for a particular onscreen layout. A high cognition load class indicates complexity in the layout design whereas a low cognition output indicates the layout to be user friendly. Present evaluation methods like user study or KLM-GOMS based model, serves as an indirect measure of goodness of layout designs. In contrast, our approach has a unique advantage as this is a direct measure of human's biological response subjected to stimuli (in our case onscreen keyboard layouts) hence more reliable.