Abstract: 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.
Bio: Gaganpreet Singh has a Masters of Science in Robotics from the University of Plymouth (UK) and a Bachelor of Engineering in Information Technology from the University of Jammu. Singh worked with ISR-Lisbon and M-ITI as researcher, along with Hi-Tech Robotic Systemz as research engineer, Webmob Information Systems as senior software engineer, National Informatics Center as programmer, and Aptech Computer Education as project consultant and trainer. In total he holds 5.5 years of experience, and worked in Machine Vision, Machine Learning, Bio-signals, and Human-Robot Interaction (HRI) domains.