Vincenzo Ronca
Papers
2
Total Citations
24
H-Index
2
About
Vincenzo Ronca is a pioneering researcher at the intersection of human factors, neuroergonomics, and advanced manufacturing systems. His work focuses on leveraging neurophysiological techniques—particularly EEG-based metrics—to quantify cognitive workload and optimize human-machine interaction in high-stakes environments. Ronca’s most-cited study (2019, 13 citations) introduced an EEG-based workload index as a taxonomic tool to evaluate the similarity of different robot-assisted surgery systems, demonstrating how neural signals can objectively assess operator strain and system usability. His forward-looking review (2025, 11 citations) systematically charts the integration of neurophysiological methods into Industry 5.0, arguing that real-time brain monitoring is essential for characterizing human factors in collaborative, human-centric production settings. By bridging cognitive neuroscience and industrial engineering, Ronca has established a framework for designing safer, more intuitive robotic systems—from surgical theaters to smart factories. His contributions are shaping the next generation of adaptive automation, where machines respond not just to commands but to the operator’s cognitive state.
Research Focus
Key Achievements
Top Papers
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