Chuhao Wu
Papers
2
Total Citations
174
H-Index
2
About
Chuhao Wu is a leading researcher at the intersection of human factors, surgical robotics, and cognitive workload assessment. His work focuses on leveraging physiological sensing—particularly eye-tracking—to quantify and improve performance in high-stakes medical training environments. Wu’s most influential contribution, “Eye-Tracking Metrics Predict Perceived Workload in Robotic Surgical Skills Training” (2019, 131 citations), established a groundbreaking method for using gaze patterns as real-time indicators of cognitive load during robotic surgery. This work has become foundational for developing adaptive training systems that respond to a surgeon’s mental state. Expanding on this, his study “Sensor-based indicators of performance changes between sessions during robotic surgery training” (2020, 43 citations) demonstrated how multimodal sensor data can track skill acquisition over time, offering objective benchmarks for surgical proficiency. Wu’s research has profound implications for reducing medical errors and accelerating expertise in robotic-assisted procedures. By translating complex physiological signals into actionable training metrics, he has helped shape a new paradigm for evidence-based surgical education. His work continues to influence human-computer interaction, cognitive ergonomics, and the future of intelligent medical training systems.
Research Focus
Key Achievements
Top Papers
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