Papers

6

Total Citations

90

H-Index

6

About

Cheyenne C. Sonntag is a pioneering researcher in surgical education and medical simulation, with a primary focus on improving the training and assessment of central venous catheterization (CVC). Her work uniquely bridges cognitive science and haptic technology to enhance procedural skill acquisition. Sonntag’s major contributions include the development and validation of the Dynamic Haptic Robotic Trainer (DHRT), a system designed to replace static manikins with dynamic, patient-variable simulations. Her landmark study, *“Looks can be Deceiving: Gaze Pattern Differences between Novices and Experts”* (30 citations), demonstrated that eye-tracking metrics can differentiate skill levels, offering a novel, objective assessment tool. She further validated the DHRT’s efficacy in translating simulation training to bedside performance in a 2019 study (17 citations). Her work on objective assessment metrics (9 citations) and predictive performance analysis using eye tracking (7 citations) has established foundational frameworks for automated, personalized feedback in surgical training. Sonntag’s research directly addresses the critical need to reduce the up to 39% adverse event rate in CVC procedures, positioning her as a key innovator in safer, data-driven medical education.

Research Focus

Key Achievements

6
H-Index
6
Papers
90
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Looks can be deceiving: Gaze pattern differences between novices and experts during placement of central lines
30 citations · 2018
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Penn State Milton S. Hershey Medical Center, Hershey (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago