Joint Torque

Joint torque, the rotational force at a joint, is a crucial parameter for understanding human and robotic movement, with research focusing on accurate prediction and estimation for applications in rehabilitation and robotics. Current efforts utilize diverse approaches, including physics-informed neural networks (PINNs), gated recurrent units (GRUs), and other machine learning techniques, often incorporating data augmentation strategies to improve model robustness and accuracy. These advancements are significant for improving the design and control of exoskeletons, prosthetics, and robotic systems, as well as for a deeper understanding of human biomechanics and motor control.