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cs.LG2025
Multi-Joint Physics-Informed Deep Learning Framework for Time-Efficient Inverse Dynamics
Shuhao Ma, Zeyi Huang, Yu Cao +4
Time-efficient estimation of muscle activations and forces across multi-joint systems is critical for clinical assessment and assistive device control. However, conventional approa…
cs.LG2024★ 36 cited
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…
cs.LG2023
The bionic neural network for external simulation of human locomotor system
Yue Shi, Shuhao Ma, Yihui Zhao
Muscle forces and joint kinematics estimated with musculoskeletal (MSK) modeling techniques offer useful metrics describing movement quality. Model-based computational MSK models c…