Muscle Synergy

Muscle synergy research investigates how the nervous system coordinates the activity of multiple muscles to produce coordinated movements, aiming to understand and replicate this efficient control strategy. Current research focuses on developing computational models, including Bayesian Gaussian processes and deep learning architectures like Koopman operators, to analyze and predict muscle activation patterns, often leveraging techniques from Riemannian geometry to account for the complex, nonlinear dynamics of the musculoskeletal system. This work has implications for improving robotic control, designing effective rehabilitation strategies, and enhancing our understanding of human motor control and learning, particularly in high-dimensional systems like the hand.