Literature DB >> 33370252

OpenSim Moco: Musculoskeletal optimal control.

Christopher L Dembia1, Nicholas A Bianco1, Antoine Falisse2,3, Jennifer L Hicks3, Scott L Delp1,3,4.   

Abstract

Musculoskeletal simulations are used in many different applications, ranging from the design of wearable robots that interact with humans to the analysis of patients with impaired movement. Here, we introduce OpenSim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation. Moco frees researchers from implementing direct collocation themselves-which typically requires extensive technical expertise-and allows them to focus on their scientific questions. The software can handle a wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which enable modeling of kinematic loops (e.g., cycling models) and complex anatomy (e.g., patellar motion). To show the abilities of Moco, we first solved for muscle activity that produced an observed walking motion while minimizing squared muscle excitations and knee joint loading. Next, we predicted how muscle weakness may cause deviations from a normal walking motion. Lastly, we predicted a squat-to-stand motion and optimized the stiffness of an assistive device placed at the knee. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand the movement of humans and other animals.

Entities:  

Year:  2020        PMID: 33370252      PMCID: PMC7793308          DOI: 10.1371/journal.pcbi.1008493

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  54 in total

Review 1.  Optimization-based models of muscle coordination.

Authors:  Boris I Prilutsky; Vladimir M Zatsiorsky
Journal:  Exerc Sport Sci Rev       Date:  2002-01       Impact factor: 6.230

2.  An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo.

Authors:  David G Lloyd; Thor F Besier
Journal:  J Biomech       Date:  2003-06       Impact factor: 2.712

3.  Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait.

Authors:  Apoorva Rajagopal; Christopher L Dembia; Matthew S DeMers; Denny D Delp; Jennifer L Hicks; Scott L Delp
Journal:  IEEE Trans Biomed Eng       Date:  2016-07-07       Impact factor: 4.538

4.  OpenSim: open-source software to create and analyze dynamic simulations of movement.

Authors:  Scott L Delp; Frank C Anderson; Allison S Arnold; Peter Loan; Ayman Habib; Chand T John; Eran Guendelman; Darryl G Thelen
Journal:  IEEE Trans Biomed Eng       Date:  2007-11       Impact factor: 4.538

5.  The contribution of passive-elastic mechanisms to lower extremity joint kinetics during human walking.

Authors:  Ben Whittington; Amy Silder; Bryan Heiderscheit; Darryl G Thelen
Journal:  Gait Posture       Date:  2007-10-24       Impact factor: 2.840

6.  Muscle-tendon mechanics explain unexpected effects of exoskeleton assistance on metabolic rate during walking.

Authors:  Rachel W Jackson; Christopher L Dembia; Scott L Delp; Steven H Collins
Journal:  J Exp Biol       Date:  2017-03-24       Impact factor: 3.312

7.  Predictive simulation of gait at low gravity reveals skipping as the preferred locomotion strategy.

Authors:  Marko Ackermann; Antonie J van den Bogert
Journal:  J Biomech       Date:  2012-02-24       Impact factor: 2.712

8.  Predictive Simulations of Neuromuscular Coordination and Joint-Contact Loading in Human Gait.

Authors:  Yi-Chung Lin; Jonathan P Walter; Marcus G Pandy
Journal:  Ann Biomed Eng       Date:  2018-04-18       Impact factor: 3.934

9.  How tibiofemoral alignment and contact locations affect predictions of medial and lateral tibiofemoral contact forces.

Authors:  Zachary F Lerner; Matthew S DeMers; Scott L Delp; Raymond C Browning
Journal:  J Biomech       Date:  2015-01-05       Impact factor: 2.712

10.  Optimality principles for model-based prediction of human gait.

Authors:  Marko Ackermann; Antonie J van den Bogert
Journal:  J Biomech       Date:  2010-01-13       Impact factor: 2.712

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  11 in total

1.  An approximate stochastic optimal control framework to simulate nonlinear neuro-musculoskeletal models in the presence of noise.

Authors:  Tom Van Wouwe; Lena H Ting; Friedl De Groote
Journal:  PLoS Comput Biol       Date:  2022-06-08       Impact factor: 4.779

Review 2.  Perspective on musculoskeletal modelling and predictive simulations of human movement to assess the neuromechanics of gait.

Authors:  Friedl De Groote; Antoine Falisse
Journal:  Proc Biol Sci       Date:  2021-03-03       Impact factor: 5.349

3.  Interactions between initial posture and task-level goal explain experimental variability in postural responses to perturbations of standing balance.

Authors:  Tom Van Wouwe; Lena H Ting; Friedl De Groote
Journal:  J Neurophysiol       Date:  2020-12-16       Impact factor: 2.714

Review 4.  Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation.

Authors:  Seungmoon Song; Łukasz Kidziński; Xue Bin Peng; Carmichael Ong; Jennifer Hicks; Sergey Levine; Christopher G Atkeson; Scott L Delp
Journal:  J Neuroeng Rehabil       Date:  2021-08-16       Impact factor: 4.262

5.  Humans use minimum cost movements in a whole-body task.

Authors:  Lijia Liu; Dana Ballard
Journal:  Sci Rep       Date:  2021-10-11       Impact factor: 4.379

6.  A direct collocation framework for optimal control simulation of pedaling using OpenSim.

Authors:  Sangsoo Park; Graham E Caldwell; Brian R Umberger
Journal:  PLoS One       Date:  2022-02-22       Impact factor: 3.240

7.  Finding Emergent Gait Patterns May Reduce Progression of Knee Osteoarthritis in a Clinically Relevant Time Frame.

Authors:  Dhruv Gupta; Cyril John Donnelly; Jeffrey A Reinbolt
Journal:  Life (Basel)       Date:  2022-07-14

8.  Prediction of Propulsion Kinematics and Performance in Wheelchair Rugby.

Authors:  David S Haydon; Ross A Pinder; Paul N Grimshaw; William S P Robertson; Connor J M Holdback
Journal:  Front Sports Act Living       Date:  2022-07-07

9.  Patterns of asymmetry and energy cost generated from predictive simulations of hemiparetic gait.

Authors:  Russell T Johnson; Nicholas A Bianco; James M Finley
Journal:  PLoS Comput Biol       Date:  2022-09-09       Impact factor: 4.779

10.  Using Bayesian inference to estimate plausible muscle forces in musculoskeletal models.

Authors:  Russell T Johnson; Daniel Lakeland; James M Finley
Journal:  J Neuroeng Rehabil       Date:  2022-03-23       Impact factor: 4.262

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