We explore Human-Machine Interaction (HMI) by developing adaptive interfaces that optimize information presentation, using real-time eye-tracking, physiological sensors, and human-drone interaction.
Our lab develops adaptive interface systems that utilize real-time eye-tracking to control information presentation in critical environments. Our dynamic cockpit display, for example, automatically hides symbols once the pilot has viewed them, leaving only essential data visible. This method aims to minimize visual clutter and cognitive load, thereby improving situational awareness and decision-making.
We work on human-drone interaction through drone programming, eye-tracking, and UI improving. Our research focuses on how pilots react to sudden signal interruptions, which turns into actionable UI improvements and training recommendations to ensure safer and more reliable operations for every pilot. We also focus on AI-powered drones by flying around crops and analyzing the recorded video with a machine learning algorithm, in order to detect key indicators of plant health with high precision.
Our lab utilizes advanced physiological sensors to measure users’ stress levels during interactions, providing valuable insights into how different conditions affect the human body. Using tools like OpenSignals, we collect and analyze data from sensors such as EDA (electrodermal activity), ECG (electrocardiography), and BVP (blood-volume pulse). These sensors help us understand physiological responses and assess the impact of various stimuli on users’ stress levels, paving the way for more personalized and effective user experiences in human-computer interactions.
Related Selected Publications
- Xenos M., Mallas A., Minas D., “Using Eye-Tracking for Adaptive Human-Machine Interfaces for Pilots: A Literature Review and Sample Cases”, Journal of Physics: Conference Series, Volume 2716, 13th EASN International Conference on: Innovation in Aviation & Space for opening New Horizons 05/09/2023 – 08/09/2023 Salerno, Italy. https://doi.org/10.1088/1742-6596/2716/1/012072
- Evangelou S. M., Michanetzi E. L., Xenos M., “Exploring the impact of negative online feedback on well-being: A comprehensive analysis incorporating Big-Five personality traits and physiological responses”, Computers in Human Behavior Reports, Volume 15, August 2024. https://doi.org/10.1016/j.chbr.2024.100457
Download the information here.