Literature DB >> 24290234

A passive movement method for parameter estimation of a musculo-skeletal arm model incorporating a modified hill muscle model.

Tung Fai Yu1, Adrian J Wilson2.   

Abstract

In this paper we present an experimental method of parameterising the passive mechanical characteristics of the bicep and tricep muscles in vivo, by fitting the dynamics of a two muscle arm model incorporating anatomically meaningful and structurally identifiable modified Hill muscle models to measured elbow movements. Measurements of the passive flexion and extension of the elbow joint were obtained using 3D motion capture, from which the elbow angle trajectories were determined and used to obtain the spring constants and damping coefficients in the model through parameter estimation. Four healthy subjects were used in the experiments. Anatomical lengths and moment of inertia values of the subjects were determined by direct measurement and calculation. There was good reproducibility in the measured arm movement between trials, and similar joint angle trajectory characteristics were seen between subjects. Each subject had their own set of fitted parameter values determined and the results showed good agreement between measured and simulated data. The average fitted muscle parallel spring constant across all subjects was 143 N/m and the average fitted muscle parallel damping constant was 1.73 Ns/m. The passive movement method was proven to be successful, and can be applied to other joints in the human body, where muscles with similar actions are grouped together.
Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Entities:  

Keywords:  Bicep; Hill muscle model; Joint trajectories; Musculo-skeletal; Parameter estimation; Passive movement; Triceps

Mesh:

Year:  2013        PMID: 24290234     DOI: 10.1016/j.cmpb.2013.11.003

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

Authors:  Ahmed Ramadan; Connor Boss; Jongeun Choi; N Peter Reeves; Jacek Cholewicki; John M Popovich; Clark J Radcliffe
Journal:  J Biomech Eng       Date:  2018-07-01       Impact factor: 2.097

2.  Quantitative Analysis of EEG Power Spectrum and EMG Median Power Frequency Changes after Continuous Passive Motion Mirror Therapy System.

Authors:  Taewoong Park; Mina Lee; Taejong Jeong; Yong-Il Shin; Sung-Min Park
Journal:  Sensors (Basel)       Date:  2020-04-21       Impact factor: 3.576

  2 in total

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