Literature DB >> 2062441

Physiological prediction of muscle forces--I. Theoretical formulation.

K R Kaufman1, K W An, W J Litchy, E Y Chao.   

Abstract

A physiological model for predicting muscle forces is described. Rigid-body mechanics and musculoskeletal physiology are used to describe the dynamics of the segment model and muscle model. Unknown muscle and joint contact forces outnumber the equilibrium equations resulting in an indeterminate problem. Mathematical optimization is utilized to resolve the indeterminacy. The modeling procedure relies entirely on established physiological principles. Data describing the muscle anatomy and body structures are included. A model defining the force-length-velocity-activation relationship of a muscle is adopted. The force a muscle produces is assumed to be proportional to its maximum stress, physiological cross-sectional area, activation, and its functional configurations including the muscle architecture, muscle length, contracting velocity, and passive tension. These factors are incorporated into inequality equations which limit the force for each muscle. Minimal muscular activation is forwarded as the optimization criterion for muscle force determination.

Mesh:

Year:  1991        PMID: 2062441     DOI: 10.1016/0306-4522(91)90012-d

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  20 in total

1.  Variation in external rotation moment arms among subregions of supraspinatus, infraspinatus, and teres minor muscles.

Authors:  Joseph E Langenderfer; Cameron Patthanacharoenphon; James E Carpenter; Richard E Hughes
Journal:  J Orthop Res       Date:  2006-08       Impact factor: 3.494

2.  Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command.

Authors:  Thomas S Buchanan; David G Lloyd; Kurt Manal; Thor F Besier
Journal:  J Appl Biomech       Date:  2004-11       Impact factor: 1.833

3.  A stochastic analysis of glenoid inclination angle and superior migration of the humeral head.

Authors:  Nicholas G Flieg; Christopher J Gatti; Lisa Case Doro; Joseph E Langenderfer; James E Carpenter; Richard E Hughes
Journal:  Clin Biomech (Bristol, Avon)       Date:  2008-02-14       Impact factor: 2.063

4.  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

Review 5.  Quantification of quadriceps and hamstring antagonist activity.

Authors:  E Kellis
Journal:  Sports Med       Date:  1998-01       Impact factor: 11.136

6.  Metabolic cost underlies task-dependent variations in motor unit recruitment.

Authors:  Adrian K M Lai; Andrew A Biewener; James M Wakeling
Journal:  J R Soc Interface       Date:  2018-11-21       Impact factor: 4.118

7.  Energy Harvesting and Sensing with Embedded Piezoelectric Ceramics in Knee Implants.

Authors:  Mohsen Safaei; R Michael Meneghini; Steven R Anton
Journal:  IEEE ASME Trans Mechatron       Date:  2018-01-15       Impact factor: 5.303

8.  Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods.

Authors:  Alexander V Terekhov; Vladimir M Zatsiorsky
Journal:  Biol Cybern       Date:  2011-02-11       Impact factor: 2.086

9.  Shoulder model validation and joint contact forces during wheelchair activities.

Authors:  Melissa M B Morrow; Kenton R Kaufman; Kai-Nan An
Journal:  J Biomech       Date:  2010-06-08       Impact factor: 2.712

10.  Constitutive modeling of skeletal muscle tissue with an explicit strain-energy function.

Authors:  G M Odegard; T L Haut Donahue; D A Morrow; K R Kaufman
Journal:  J Biomech Eng       Date:  2008-12       Impact factor: 2.097

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.