Jintao Lei
Papers
2
Total Citations
4
H-Index
2
About
Jintao Lei is at the forefront of advancing robotic-assisted orthopedic surgery, with a focused expertise in the precise control of fracture reduction robots. His research addresses a critical challenge in the field: ensuring accurate position and force tracking despite the complex, variable forces of muscle tension and uncertain robot dynamics. Lei’s major contributions include the development of a neural network adaptive admittance control system, which significantly enhances a robot's ability to maintain both position and force accuracy under large, unpredictable loads. He has further refined this approach by integrating a nonlinear disturbance observer with a Radial Basis Function neural network, creating a robust control method that actively compensates for dynamic disturbances. Though his most-cited works are recent, each accumulating 2 citations, they represent foundational advances in a high-stakes application. By tackling the core issues of compliance and tracking fidelity, Lei’s research is paving the way for more reliable, autonomous, and clinically effective fracture reduction procedures, promising to improve surgical outcomes and reduce the physical demands on surgeons.
Research Focus
Key Achievements
Top Papers
- 1
- 2