Dinghao Xue
Papers
1
Total Citations
11
H-Index
1
About
Dinghao Xue is a leading researcher in the field of robotic prostheses and intelligent locomotion control, with a particular focus on small-data-driven machine learning for assistive technologies. His most notable contribution is the development of the Temporal Convolutional Capsule Network (TCCN), a novel architecture that integrates spatial-temporal processing with dilated convolutions to achieve highly accurate locomotion mode recognition for robotic lower-limb prostheses. This work, published in 2022 and garnering 11 citations, addresses a critical challenge in the field: enabling precise prosthetic control under diverse walking conditions using limited training data. Xue’s approach significantly advances the real-world applicability of smart prosthetics by improving their adaptability and responsiveness. His research bridges the gap between advanced neural network design and practical rehabilitation engineering, offering a scalable solution for personalized assistive devices. With a growing citation impact, Xue is recognized for pushing the boundaries of data-efficient learning in biomechatronics, making him a promising figure in the intersection of artificial intelligence and human mobility restoration.
Research Focus
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Top Papers
- 1