Frederik Cornillie
Papers
2
Total Citations
43
H-Index
2
About
Frederik Cornillie is a leading researcher at the intersection of cognitive neuroscience and industrial engineering, specializing in the real-time detection of cognitive overload in complex work environments. His pioneering work focuses on leveraging electroencephalography (EEG) and electrooculography (EOG) to monitor mental states in Industry 4.0 settings, where human-machine collaboration demands heightened cognitive flexibility. Cornillie’s major contributions include developing predictive EEG features that identify cognitive overload in assembly workers, a critical advancement for preventing errors and enhancing safety in automated factories. His 2022 paper, “Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context,” has garnered 29 citations, while his foundational 2019 study on predictive EEG features has been cited 14 times. By demonstrating how neural signals can be harnessed to optimize human performance alongside robotics, Cornillie’s work directly addresses the challenges of an increasingly automated workforce. His research not only advances neuroergonomics but also provides practical tools for designing adaptive workstations that respond to workers’ mental states, making him a key figure in shaping the future of safe, efficient industrial operations.
Research Focus
Key Achievements
Top Papers
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