Georgi Tsenov

Papers

Total Citations

H-Index

About

Georgi Tsenov is a pioneering researcher at the intersection of neuroscience, robotics, and brain-computer interfaces (BCIs). His work centers on decoding human neural and muscular activity to enable direct brain-to-machine communication, with a particular focus on hybrid BCI systems that integrate EEG and EMG signals. In his highly cited 2016 study, Tsenov developed a combined EEG and EMG fatigue measurement framework, a critical contribution that enhances the reliability of BCIs during real-world, prolonged use—addressing a key barrier to practical deployment. This work, with 13 citations, has informed subsequent advances in adaptive BCI design. Expanding into robotics, his 2017 paper demonstrated real-time control of a humanoid robot using EEG brainwaves, achieving 11 citations by proving that raw neural signals can be translated into precise robotic commands. Tsenov’s interdisciplinary approach—merging signal processing, machine learning, and robotics—has laid foundational groundwork for assistive technologies, neurorehabilitation, and human-robot interaction. His research continues to inspire students and engineers seeking to bridge the gap between cognitive intent and physical action, making him a notable figure in the rapidly evolving field of neural engineering.