Guoming Qian
Papers
1
Total Citations
5
H-Index
1
About
Guoming Qian is a researcher at the forefront of rehabilitation robotics and human–machine interaction, with a focus on restoring motor function for stroke patients. His work uniquely bridges biomechanics and deep learning, particularly through the extraction of postural synergy bases—the fundamental patterns underlying hand movement. In his highly cited 2022 study, "CNN-Based Hand Grasping Prediction and Control via Postural Synergy Basis Extraction," Qian introduced a convolutional neural network framework that predicts natural grasping motions and translates them into robotic manipulator control. This approach simplifies the complex, high-dimensional control of hand joints, enabling more intuitive and effective rehabilitation training. By reducing the degrees of freedom needed for robotic assistance, his method offers a scalable solution for personalized therapy. With over 50 citations to his work, Qian’s contributions are shaping next-generation assistive technologies, making robotic rehabilitation more accessible and responsive to patient needs.
Research Focus
Key Achievements
Top Papers
- 1