Boce Hu
Papers
1
Total Citations
7
H-Index
1
About
Boce Hu is a researcher at the forefront of rehabilitation engineering and human movement science, with a particular focus on trunk stability and assistive technologies. His most cited work, "A Deep-Learning Based Real-Time Prediction of Seated Postural Limits and Its Application in Trunk Rehabilitation" (2022, 7 citations), introduces a novel approach to defining the seated postural limit—the boundary beyond which a person cannot return to a neutral trunk position without external support. By leveraging deep learning for real-time prediction, Hu’s research enables personalized, adaptive assistive support for individuals with trunk impairments, directly enhancing rehabilitation outcomes. This work bridges computational modeling and clinical application, offering a data-driven framework to improve safety and independence for patients with spinal cord injuries or neuromuscular disorders. Hu’s contributions are particularly notable for their translational potential, providing a foundation for smart rehabilitation systems that respond dynamically to a user’s postural capabilities. His research underscores a commitment to integrating artificial intelligence with biomechanics, making him a rising voice in the field of human-centered rehabilitation technology.
Research Focus
Key Achievements
Top Papers
- 1