36 citations · 39 across the 5 of their papers we have counts for
5 papers
Physics-Embedded Neural Networks for sEMG-based Continuous Motion Estimation
Wending Heng, Chaoyuan Liang, Yihui Zhao +3
Accurately decoding human motion intentions from surface electromyography (sEMG) is essential for myoelectric control and has wide applications in rehabilitation robotics and assis…
Instance-Based Transfer Learning with Similarity-Aware Subject Selection for Cross-Subject SSVEP-Based BCIs
Ziwen Wang, Yue Zhang, Zhiqiang Zhang +4
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) can achieve high recognition accuracy with sufficient training data. Transfer learning presents…
Knowledge-Based Deep Learning for Time-Efficient Inverse Dynamics
Shuhao Ma, Yu Cao, Ian D. Robertson +3
Accurate understanding of muscle activation and muscle forces plays an essential role in neuro-rehabilitation and musculoskeletal disorder treatments. Computational musculoskeletal…
Physics-informed Deep Learning for Muscle Force Prediction with Unlabeled sEMG Signals
Shuhao Ma, Jie Zhang, Chaoyang Shi +3
Computational biomechanical analysis plays a pivotal role in understanding and improving human movements and physical functions. Although physics-based modeling methods can interpr…
Motion-Driven Neural Optimizer for Prophylactic Braces Made by Distributed Microstructures
Xingjian Han, Yu Jiang, Weiming Wang +9
Joint injuries, and their long-term consequences, present a substantial global health burden. Wearable prophylactic braces are an attractive potential solution to reduce the incide…