Filippo Rigoni
Papers
1
Total Citations
2
H-Index
1
About
Filippo Rigoni is a researcher at the forefront of neuroergonomics and human-robot interaction, with a specialized focus on mental workload assessment in high-stakes environments. His most cited work, "EEG-Based Stress Assessment During Robot Assisted Surgery," introduces an adaptive pipeline for processing electroencephalographic (EEG) signals to evaluate cognitive load during surgical robot training. This contribution is notable for its innovative use of statistical methods alongside machine learning, moving beyond traditional approaches to offer real-time, objective stress monitoring. By integrating feature extraction, selection, and classification, Rigoni’s research provides a robust framework for enhancing operator performance and safety in robotic surgery. With 2 citations, this study is gaining traction as a foundational piece for future work in adaptive human-machine systems. Rigoni’s work bridges neuroscience and engineering, offering practical tools for training and error reduction. His achievements underscore a commitment to improving human factors in technology-driven fields, making his research essential reading for students and professionals exploring EEG-based cognitive state assessment and its applications in critical domains like surgery.
Research Focus
Key Achievements
Top Papers
- 1