Nicolina Sciaraffa

Papers

Total Citations

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About

Nicolina Sciaraffa is a researcher at the intersection of cognitive neuroscience and human-robot interaction, with a primary focus on using electroencephalography (EEG) to quantify mental workload in complex operational environments. Her most cited work, "EEG-Based Workload Index as a Taxonomic Tool to Evaluate the Similarity of Different Robot-Assisted Surgery Systems" (2019, 13 citations), introduces a novel methodological framework that leverages EEG-derived workload indices to assess and compare the cognitive demands imposed by different robotic surgery platforms. This contribution is significant because it moves beyond subjective self-reports or simple performance metrics, offering an objective, neurophysiological taxonomy for evaluating system design and operator training. By demonstrating that EEG workload patterns can serve as a sensitive tool for discriminating between surgical systems, Sciaraffa’s research has implications for improving patient safety, optimizing human-machine interfaces, and informing the development of more intuitive robotic technologies. Her work bridges engineering, neuroscience, and clinical practice, providing a rigorous, data-driven approach to understanding how the brain adapts to increasingly automated and complex tasks. For students and researchers, Sciaraffa exemplifies how neuroergonomic methods can be applied to real-world challenges, making her a key voice in the evolving field of cognitive engineering.