Papers
17
Total Citations
638
H-Index
10
About
Lora Cavuoto is a leading researcher in human factors engineering, with a focus on optimizing surgical performance and team dynamics in robot-assisted surgery (RAS). Her work bridges the gap between technology and human interaction, addressing critical challenges in the operating room. Cavuoto’s major contributions include developing the IDEAL framework for surgical robotics, which provides a structured approach for evaluating new technologies from development to long-term monitoring. She has also pioneered the use of computer vision techniques to automatically assess surgical performance from console-feed videos, a breakthrough that could revolutionize surgical training. Her studies on anticipation, teamwork, and cognitive load during RAS have revealed how familiarity between team members and anticipation of surgical steps can enhance efficiency and reduce errors. With over 600 citations across her top papers, Cavuoto’s research has had a significant impact on understanding workflow interruptions, communication variability, and ambulatory movements in the robotic OR. Her work on virtual reality simulators for procedures like percutaneous nephrolithotomy further demonstrates her commitment to improving surgical education. Cavuoto’s findings are essential for designing safer, more efficient surgical environments.
Research Focus
Key Achievements
Top Papers
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- 10Development and face validation of a virtual camera navigation task trainer14 citations · 2018