Sena Arman
Papers
1
Total Citations
9
H-Index
1
About
Sena Arman is a researcher at the intersection of neuroscience and surgical performance, whose work explores how functional brain networks can be used to assess and enhance surgeon capabilities. Her key research areas include neuroergonomics, cognitive load measurement, and the impact of distractions on surgical expertise. In her most-cited paper, "Association between Functional Brain Network Metrics and Surgeon Performance and Distraction in the Operating Room" (2021, 9 citations), Arman pioneered the use of electroencephalogram (EEG) features to capture dynamic changes in surgical trainees' brain networks during robot-assisted surgery. This work demonstrated that specific neural metrics can reliably evaluate both performance quality and distraction levels in real-time, offering a novel, objective approach to surgical training and safety. By linking brain connectivity patterns directly to operative outcomes, Arman’s contributions provide a foundation for developing adaptive training systems and cognitive monitoring tools in high-stakes medical environments. Her research holds significant promise for reducing errors and improving surgeon resilience, making her a notable voice in the emerging field of surgical neuroergonomics.
Research Focus
Key Achievements
Top Papers
- 1