Mary Yovanoff
Papers
10
Total Citations
162
H-Index
8
About
Mary Yovanoff is a pioneering researcher at the intersection of medical education, virtual reality, and haptic robotics. Her primary research focuses on developing advanced simulation technologies to improve surgical training, specifically for high-risk procedures like central venous catheterization (CVC). Yovanoff’s major contributions include designing the Dynamic Haptic Robotic Training (DHRT) simulator, which provides personalized, dynamic feedback to surgical residents—a significant leap from static mannequins. Her work demonstrates that high-fidelity haptic simulators can distinguish expert performance and measurably improve needle insertion skills. With over 160 combined citations across her top papers, her research has shown that such simulators reduce complication rates and enhance learning gains. Notably, her 2017 study on personalized user interfaces for haptic robotic trainers has been cited 28 times, highlighting its impact on tailoring medical education. Yovanoff has also advanced the field by integrating cadaver-derived needle forces into her simulators, ensuring realistic tissue interaction. Her achievements underscore a commitment to safer, more effective surgical training, directly addressing the learning curves faced by new residents.
Research Focus
Key Achievements
Top Papers
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- 4Improving Medical Education18 citations · 2016
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- 9Integrating Cadaver Needle Forces Into a Haptic Robotic Simulator7 citations · 2017
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