Dynamic optimization of human walking.

By Frank C. Anderson, Marcus G. Pandy. Journal of Biomechanical Engineering, 2001

1,184 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Orthopedics and Sports Medicine

View Paper: https://www.semanticscholar.org/paper/b1d05a8eacafec3edd28eae4bc8c202f0bd1dc5a

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In Biomedical Engineering

In Orthopedics and Sports Medicine

Citations in the corpus

OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange (2011, neutral): “Even half a gait cycle has shown to be practically intractable requiring over 10,000 CPU hours on a 32-CPU super-computer [25].”
Optimizing Locomotion Controllers Using Biologically-Based Actuators and Objectives (2012, background): “Simulation studies on detailed 3D musculoskeletal models have been employed to understand muscle functions during locomotion tasks [Anderson and Pandy 2001; Liu et al. 2008; Hamner et al. 2010].”
Muscular strategy shift in human running: dependence of running speed on hip and ankle muscle performance (2012, methodology): “However, the values of activation and deactivation time constants used in model simulations reported in the literature have ranged from 10 to 22ms and 30 to 200ms, respectively (Anderson and Pandy, 2001; Chumanov et al., 2007; Seth and Pandy, 2007; Zajac, 1989).”
Constraint-Based Exclusion of Limb Poses for Reconstructing Theropod Dinosaur Locomotion (2009, background): “Optimization-based simulation approaches (e.g., Anderson and Pandy, 2001; Sellers et al., 2005; Sellers and Manning, 2007) are promising avenues, but depend on accurate identification of optimization criteria, information about many more input parameters, and validation with actual kinematics and…”
Evidence for the Flexible Sensorimotor Strategies Predicted by Optimal Feedback Control (2007, background): “The ho-ReceivedMarch15 mogeneous cost could be energy consumption (Nelson, 1983; Anderson and Pandy, 2001), derivative of hand acceleration (Flash and Hogan, 1985), derivative of joint torque (Uno et al., 1989), endpoint variance (Harris and Wolpert, 1998).”
Individual muscle contributions to support in normal walking. (2003, methodology): “Although the issue of support has been addressed previously, most notably by Winter [2], Mochon and McMahon [5,6], Pandy and Berme [7 /9], Perry [4], Kepple et al. [10], Meinders et al. [26], Riley et al. [12], and Neptune et al. [11], detailed knowledge of how individual muscles generate support ha”
Review of assistive strategies in powered lower-limb orthoses and exoskeletons (2015, background): “In the literature, most of the assistive strategies aim to provide assistance in the sagittal plane, which is the one with higher dynamic and energy exchanges between the limb segments and the ground [99], but this is not sufficient to provide stability support.”
Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command. (2004, methodology): “Although optimization methods are more commonly used for inverse dynamic models, performance-based cost functions such as selecting muscles that will maximize jumping height or minimize metabolic energy have been used in forward dynamic models (e.g., Anderson & Pandy, 2001; Pandy & Zajac, 1991).”
Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System (2005, methodology): “The most popular approach has been to optimize, in an open loop, the sequence of control signals (Chow & Jacobson, 1971; Hatze & Buys, 1977; Anderson & Pandy, 2001) or limb states (Nelson, 1983; Flash & Hogan, 1985; Uno, Kawato, & Suzuki, 1989; Harris & Wolpert, 1998).”
Predictive dynamics: an optimization-based novel approach for human motion simulation (2010, methodology): “Forward dynamics can be used to solve equations of motion in modeling human motion (Roussel et al. 1998; Chevallereau et al. 1998; Anderson and Pandy 2001a).”