Literature DB >> 16513124

A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement.

Ajay Seth1, Marcus G Pandy.   

Abstract

A neuromusculoskeletal tracking (NMT) method was developed to estimate muscle forces from observed motion data. The NMT method combines skeletal motion tracking and optimal neuromuscular tracking to produce forward simulations of human movement quickly and accurately. The skeletal motion tracker calculates the joint torques needed to actuate a skeletal model and track observed segment angles and ground forces in a forward simulation of the motor task. The optimal neuromuscular tracker resolves the muscle redundancy problem dynamically and finds the muscle excitations (and muscle forces) needed to produce the joint torques calculated by the skeletal motion tracker. To evaluate the accuracy of the NMT method, kinematics and ground forces obtained from an optimal control (parameter optimization) solution for maximum-height jumping were contaminated with both random and systematic noise. These data served as input observations to the NMT method as well as an inverse dynamics analysis. The NMT solution was compared to the input observations, the original optimal solution, and a simulation driven by the inverse dynamics torques. The results show that, in contrast to inverse dynamics, the NMT method is able to produce an accurate forward simulation consistent with the optimal control solution. The NMT method also requires 3 orders-of-magnitude less CPU time than parameter optimization. The speed and accuracy of the NMT method make it a promising new tool for estimating muscle forces using experimentally obtained kinematics and ground force data.

Entities:  

Mesh:

Year:  2006        PMID: 16513124     DOI: 10.1016/j.jbiomech.2005.12.017

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  14 in total

1.  Dynamics model for analyzing reaching movements during active and passive torso rotation.

Authors:  Simone B Bortolami; Pascale Pigeon; Paul Dizio; James R Lackner
Journal:  Exp Brain Res       Date:  2008-03-11       Impact factor: 1.972

2.  Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement.

Authors:  Jennifer L Hicks; Thomas K Uchida; Ajay Seth; Apoorva Rajagopal; Scott L Delp
Journal:  J Biomech Eng       Date:  2015-01-26       Impact factor: 2.097

3.  Reactive control and its operation limits in responding to a novel slip in gait.

Authors:  Feng Yang; Yi-Chung Pai
Journal:  Ann Biomed Eng       Date:  2010-06-05       Impact factor: 3.934

4.  OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange.

Authors:  Ajay Seth; Michael Sherman; Jeffrey A Reinbolt; Scott L Delp
Journal:  Procedia IUTAM       Date:  2011

5.  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

6.  A rolling constraint reproduces ground reaction forces and moments in dynamic simulations of walking, running, and crouch gait.

Authors:  Samuel R Hamner; Ajay Seth; Katherine M Steele; Scott L Delp
Journal:  J Biomech       Date:  2013-05-21       Impact factor: 2.712

7.  Limitations of parallel global optimization for large-scale human movement problems.

Authors:  Byung-Il Koh; Jeffrey A Reinbolt; Alan D George; Raphael T Haftka; Benjamin J Fregly
Journal:  Med Eng Phys       Date:  2008-11-25       Impact factor: 2.242

8.  Optimal estimation of dynamically consistent kinematics and kinetics for forward dynamic simulation of gait.

Authors:  C David Remy; Darryl G Thelen
Journal:  J Biomech Eng       Date:  2009-03       Impact factor: 2.097

9.  Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking.

Authors:  Gil Serrancolí; Allison L Kinney; Benjamin J Fregly; Josep M Font-Llagunes
Journal:  J Biomech Eng       Date:  2016-08-01       Impact factor: 2.097

10.  A predictive model of muscle excitations based on muscle modularity for a large repertoire of human locomotion conditions.

Authors:  Jose Gonzalez-Vargas; Massimo Sartori; Strahinja Dosen; Diego Torricelli; Jose L Pons; Dario Farina
Journal:  Front Comput Neurosci       Date:  2015-09-17       Impact factor: 2.380

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.