Muscle Dynamic

Muscle dynamics research focuses on understanding the complex interplay between neural signals, muscle activation, and resulting movement, aiming to improve models of human and robotic locomotion. Current research employs diverse approaches, including physics-informed deep learning models (e.g., incorporating musculoskeletal models into neural networks), and reinforcement learning algorithms to optimize movement control and predict muscle behavior from surface electromyography (sEMG) data. These advancements have implications for improving clinical diagnostics, designing more robust and adaptable robots, and enhancing athletic performance through personalized training strategies.