Literature DB >> 11264828

A Dynamic Optimization Solution for Vertical Jumping in Three Dimensions.

FRANK C. Anderson1, MARCUS G. Pandy.   

Abstract

A three-dimensional model of the human body is used to simulate a maximal vertical jump. The body is modeled as a 10-segment, 23 degree-of-freedom (dof), mechanical linkage, actuated by 54 muscles. Six generalized coordinates describe the position and orientation of the pelvis relative to the ground; the remaining nine segments branch in an open chain from the pelvis. The head, arms, and torso (HAT) are modeled as a single rigid body. The HAT articulates with the pelvis via a 3 dof ball-and-socket joint. Each hip is modeled as a 3 dof ball-and-socket joint, and each knee is modeled as a 1 dof hinge joint. Each foot is represented by a hindfoot and toes segment. The hindfoot articulates with the shank via a 2 dof universal joint, and the toes articulate with the hindfoot via a 1 dof hinge joint. Interaction of the feet with the ground is modeled using a series of spring-damper units placed under the sole of each foot. The path of each muscle is represented by either a series of straight lines or a combination of straight lines and space curves. Each actuator is modeled as a three-element, Hill-type muscle in series with tendon. A first-order process is assumed to model muscle excitation-contraction dynamics. Dynamic optimization theory is used to calculate the pattern of muscle excitations that produces a maximal vertical jump. Quantitative comparisons between model and experiment indicate that the model reproduces the kinematic, kinetic, and muscle-coordination patterns evident when humans jump to their maximum achievable heights.

Entities:  

Year:  1999        PMID: 11264828     DOI: 10.1080/10255849908907988

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  73 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

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Authors:  Byung-Il Koh; Alan D George; Raphael T Haftka; Benjamin J Fregly
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6.  Are patient-specific joint and inertial parameters necessary for accurate inverse dynamics analyses of gait?

Authors:  Jeffrey A Reinbolt; Raphael T Haftka; Terese L Chmielewski; Benjamin J Fregly
Journal:  IEEE Trans Biomed Eng       Date:  2007-05       Impact factor: 4.538

7.  Muscular coordination of knee motion during the terminal-swing phase of normal gait.

Authors:  Allison S Arnold; Darryl G Thelen; Michael H Schwartz; Frank C Anderson; Scott L Delp
Journal:  J Biomech       Date:  2007-06-18       Impact factor: 2.712

8.  Muscle contributions to frontal plane angular momentum during walking.

Authors:  Richard R Neptune; Craig P McGowan
Journal:  J Biomech       Date:  2016-07-22       Impact factor: 2.712

9.  An analytical approach to the problem of inverse optimization with additive objective functions: an application to human prehension.

Authors:  Alexander V Terekhov; Yakov B Pesin; Xun Niu; Mark L Latash; Vladimir M Zatsiorsky
Journal:  J Math Biol       Date:  2009-11-10       Impact factor: 2.259

10.  Muscle contributions to fore-aft and vertical body mass center accelerations over a range of running speeds.

Authors:  Samuel R Hamner; Scott L Delp
Journal:  J Biomech       Date:  2012-12-11       Impact factor: 2.712

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