Literature DB >> 11447064

Computer modeling and simulation of human movement.

M G Pandy1.   

Abstract

Recent interest in using modeling and simulation to study movement is driven by the belief that this approach can provide insight into how the nervous system and muscles interact to produce coordinated motion of the body parts. With the computational resources available today, large-scale models of the body can be used to produce realistic simulations of movement that are an order of magnitude more complex than those produced just 10 years ago. This chapter reviews how the structure of the neuromusculoskeletal system is commonly represented in a multijoint model of movement, how modeling may be combined with optimization theory to simulate the dynamics of a motor task, and how model output can be analyzed to describe and explain muscle function. Some results obtained from simulations of jumping, pedaling, and walking are also reviewed to illustrate the approach.

Entities:  

Mesh:

Year:  2001        PMID: 11447064     DOI: 10.1146/annurev.bioeng.3.1.245

Source DB:  PubMed          Journal:  Annu Rev Biomed Eng        ISSN: 1523-9829            Impact factor:   9.590


  55 in total

1.  Simple and complex models for studying muscle function in walking.

Authors:  Marcus G Pandy
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2003-09-29       Impact factor: 6.237

2.  Joint kinetic response during unexpectedly reduced plantar flexor torque provided by a robotic ankle exoskeleton during walking.

Authors:  Pei-Chun Kao; Cara L Lewis; Daniel P Ferris
Journal:  J Biomech       Date:  2010-02-19       Impact factor: 2.712

3.  Evaluation of parallel decomposition methods for biomechanical optimizations.

Authors:  Byung Il Koh; Jeffrey A Reinbolt; Benjamin J Fregly; Alan D George
Journal:  Comput Methods Biomech Biomed Engin       Date:  2004-08       Impact factor: 1.763

4.  Parallel asynchronous particle swarm optimization.

Authors:  Byung-Il Koh; Alan D George; Raphael T Haftka; Benjamin J Fregly
Journal:  Int J Numer Methods Eng       Date:  2006-07-23       Impact factor: 3.477

5.  Simulated hip abductor strengthening reduces peak joint contact forces in patients with total hip arthroplasty.

Authors:  Casey A Myers; Peter J Laz; Kevin B Shelburne; Dana L Judd; Joshua D Winters; Jennifer E Stevens-Lapsley; Bradley S Davidson
Journal:  J Biomech       Date:  2019-06-06       Impact factor: 2.712

6.  Evidence for the flexible sensorimotor strategies predicted by optimal feedback control.

Authors:  Dan Liu; Emanuel Todorov
Journal:  J Neurosci       Date:  2007-08-29       Impact factor: 6.167

Review 7.  Constraints on the complete optimization of human motion.

Authors:  Paul S Glazier; Keith Davids
Journal:  Sports Med       Date:  2009       Impact factor: 11.136

8.  Evaluation of a particle swarm algorithm for biomechanical optimization.

Authors:  Jaco F Schutte; Byung-Il Koh; Jeffrey A Reinbolt; Raphael T Haftka; Alan D George; Benjamin J Fregly
Journal:  J Biomech Eng       Date:  2005-06       Impact factor: 2.097

9.  Choosing the fastest movement: perceiving speed-accuracy tradeoffs.

Authors:  Scott J Young; Jay Pratt; Tom Chau
Journal:  Exp Brain Res       Date:  2007-11-08       Impact factor: 1.972

10.  Motion control of musculoskeletal systems with redundancy.

Authors:  Hyunjoo Park; Dominique M Durand
Journal:  Biol Cybern       Date:  2008-11-05       Impact factor: 2.086

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.