We developed a framework for Physiologically Attentive User Interfaces, to reduce the interaction gap between humans and machines in life critical robot teleoperations. Our system utilizes emotional state awareness capabilities of psychophysiology and classifies three emotional states (Resting, Stress, and Workload) by analysing physiological data along with facial expression and eye movement analysis. This emotional state estimation is then used to create a dynamic interface that updates in real time with respect to user’s emotional state. The results of a preliminary evaluation of the developed emotional state classifier for robot teleoperation are presented, along with its future possibilities are discussed.

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Psychophysiology,Biosignals,Bitalino,Robot teleoperation,Facial emotions,Electroencephalography,Electrocardiogram,Electrodermal activity,Electromyography,Eye tracking,Sikuli,Picture-driven computing,Automation,ISI,Emotions

• Ciências Físicas - Ciências Naturais