Papers
2
Total Citations
6
H-Index
2
About
Chenhao Cao is a rising researcher at the forefront of human–machine interaction (HMI) and biomechanical sensing, whose work bridges the gap between biological signal processing and robotic design. His key research areas include multimodal biological signal analysis, dynamic movement recognition, and high-resolution 3D scanning for hand-object interaction studies. Cao’s major contributions are twofold: first, he developed a high-precision dynamic movement recognition algorithm that fuses multimodal biological signals—such as electromyography and motion data—to overcome the limitations of single-modal approaches, achieving robust feature representation and noise resilience for seamless HMI. Second, he created a whole-body, high-resolution dataset of hand-object contact areas using advanced 3D scanning methods, providing unprecedented detail on human hand operation patterns. This dataset, with its 2 citations already, is poised to guide the design of hand-related sensors and robots, as well as predict object properties. His most cited work (4 citations) has been recognized for its potential to revolutionize interactive systems. Cao’s innovative fusion of signal processing and 3D scanning marks him as a key contributor to next-generation HMI and robotic dexterity research.
Research Focus
Key Achievements
Top Papers
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