Ioannis Zoulias
Papers
2
Total Citations
26
H-Index
2
About
Ioannis Zoulias is a pioneering researcher at the intersection of brain-computer interfaces (BCI), virtual reality, and rehabilitation robotics. His most cited work introduces a novel autocorrelation analysis of EEG signals to decode movement intention, enabling patients to actively control soft robotic rehabilitation systems through thought alone. This 2016 study, with 24 citations, demonstrates how BCI can transform passive therapy into active, neuroplasticity-driven recovery by allowing users to initiate movement commands directly from their brain activity. More recently, Zoulias has extended his expertise to human-robot interaction, developing data-driven methods to estimate operator error rates in telemanipulation systems using skeletal position tracking. This 2024 work addresses critical safety challenges in industrial telerobotics by generating behavioral estimations from observed operator features. His research uniquely bridges neural signal processing with practical rehabilitation and industrial applications, showing how brain and body signals can optimize human-machine collaboration. By combining rigorous signal analysis with real-world implementation, Zoulias contributes to making robotic systems more intuitive, responsive, and safe for both medical and industrial users.
Research Focus
Key Achievements
Top Papers
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