Papers
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Total Citations
28
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About
Bingrong Chen is a leading researcher at the intersection of robotics, artificial intelligence, and spine surgery, with a primary focus on advancing robot-assisted surgical systems. His most-cited work, "Force Perception and Bone Recognition of Vertebral Lamina Milling by Robot-Assisted Ultrasonic Bone Scalpel Based on Backpropagation Neural Network" (2021, 28 citations), exemplifies his key contribution: developing intelligent force perception technologies that enable surgical robots to quantify tactile sensations during bone milling. By integrating backpropagation neural networks, Chen has pioneered methods that allow robots to recognize bone layers and adapt milling forces in real time, significantly enhancing the safety and precision of spinal procedures. This work addresses a critical challenge in minimally invasive spine surgery—the need for accurate, real-time feedback to prevent damage to neural structures. Chen’s research has been instrumental in translating AI-driven tactile sensing from concept to clinical application, demonstrating how machine learning can bridge the gap between human surgical expertise and robotic execution. His achievements are particularly notable for their potential to reduce surgical errors and improve patient outcomes in complex vertebral surgeries.
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