Generating dynamic simulations of movement using computed muscle control.

By Darryl G. Thelen, Frank C. Anderson, Scott L. Delp. Journal of Biomechanics, 2003

709 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/82ac507706388940be50e490f4560c92b3f2046a

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In Biomedical Engineering

In Cognitive Neuroscience

Citations in the corpus

Resolving actuator redundancy - optimal control vs. control allocation (2005, background): “Similar control distribution concepts can also be found in biomechanical muscle control [30], cement mixing [32], and yaw stability control ? This paper was presented at the European Control Conference 2003.”
Automated Machine Learning: Methods, Systems, Challenges (2019, positive): “An overall estimate of muscle effort was calculated using the sum of muscle activations squared, a commonly used metric in biomechanical studies [8, 48].”
Analysis of musculoskeletal systems in the AnyBody Modeling System (2006, background): “The first experiments with combinations of forward and inverse dynamic methods are being done these years, see for instance [27], and maybe such approaches can eliminate some of the above-mentioned restrictions, retaining some efficiency from the inverse dynamics approach.”
OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange (2011, neutral): “The computed muscle control algorithm [9] is implemented in OpenSim as a specialized Controller and described in Fig.”
Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement. (2015, methodology): “, in Computed Muscle Control [42]) or a force balance is calculated (e.”
Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait (2016, methodology): “The smoothed kinematics were input into the computed muscle control (CMC) algorithm [46], which uses forward simulation and a feedback controller that tracks the input kinematics to calculate muscle excitations, muscle activations, and muscle forces.”
OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement (2018, background): “Neurophysiological structures and controllers, such as goal-directed and tracking (Computed Muscle Control; CMC) controllers [50] and a reflex controller [20], enable users to generate muscle-driven simulations of observed motions and to predict human and animal movement.”
EMG-Driven Forward-Dynamic Estimation of Muscle Force and Joint Moment about Multiple Degrees of Freedom in the Human Lower Extremity (2012, neutral): “generalizable across subjects and motor tasks [1,2,3].”
OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement (2007, methodology): “For example, the computed muscle control technique determines muscle excitations that reproduce measured pedaling dynamics in just ten minutes [ 28 ]; this is over two orders of magnitude faster than conventional dynamic optimization techniques.”
Muscle contributions to propulsion and support during running (2010, methodology): “The computed muscle control algorithm (Thelen et al., 2003; Thelen and Anderson, 2006) was then used to compute the muscle excitations required to track the kinematics produced by RRA.”
Model-based estimation of muscle forces exerted during movements. (2007, methodology): “Thelen et al. (2003) imple mented static optimization into a feedback control system to minimize tracking errors in joint kinematics during cycling by minimizing the sum of the squared muscle acti vations at each step of the forward dynamic solution.”