Jiaxun Cao
Papers
1
Total Citations
7
H-Index
1
About
Jiaxun Cao is a leading researcher in the field of wearable robotics and human-robot interaction, with a primary focus on locomotion mode recognition for lower limb exoskeletons. His most notable contribution is the development of a SE-DenseNet-LSTM hybrid model, which integrates a dense convolutional network (DenseNet) with long short-term memory (LSTM) and a squeeze-and-excitation (SE) channel attention mechanism. This innovative approach significantly enhances the accuracy and adaptability of locomotion mode recognition—a critical component for flexible, real-time control in powered exoskeletons. Since its publication in 2024, the work has already garnered 7 citations, underscoring its immediate impact on the field. Cao’s research bridges deep learning and biomechanical control, offering a robust solution for decoding human movement intent. His work is particularly influential for advancing assistive technologies in rehabilitation and mobility augmentation, making him a rising figure in the intersection of artificial intelligence and wearable robotics.
Research Focus
Key Achievements
Top Papers
- 1