Effects of Neuromuscular Strength Training on Vertical Jumping Performance - A Computer Simulation Study
Catherine
Lloyd
Auckland Bioengineering Institute, The University of Auckland
Model Status
This CellML model runs in OpenCell and COR to recreate the published results. The units have been checked and they are consistent.
Model Structure
ABSTRACT: The purpose of this study was twofold: (a) to systematically investigate the effect of altering specific neuromuscular parameters on maximum vertical jump height, and (b) to systematically investigate the effect of strengthening specific muscle groups on maximum vertical jump height. A two-dimensional musculoskeletal model which consisted of four rigid segments, three joints, and six Hill-type muscle models, representing the six major muscles and muscle groups in the lower extremity that contribute to jumping performance, was trained systematically. Maximum isometric muscle force, maximum muscle shortening velocity, and maximum muscle activation, which were manipulated to simulate the effects of strength training, all had substantial effects on jumping performance. Part of the increase in jumping performance could be explained solely by the interaction between the three neuromuscular parameters. It appeared that the most effective way to improve jumping performance was to train the knee extensors among all lower extremity muscles. For the model to fully benefit from any training effects of the neuromuscular system, it was necessary to continue to reoptimize the muscle coordination, in particular after the strength training sessions that focused on increasing maximum isometric muscle force.
The original paper is cited below:
Effects of Neuromuscular Strength Training on Vertical Jumping Performance - A Computer Simulation Study, Akinori Nagano and Karin G.M. Gerritsen, 2001, Journal of Applied Biomechanics, 17, 113-128. (there is no PubMed ID for this article).
A two-component of skeletal muscle with the contractile element defined by Hill equations for concentric contraction.
$\mathrm{F\_isom}=c\left(\frac{\mathrm{L\_ce}}{\mathrm{L\_ce\_opt}}\right)^{2}-\frac{2c\mathrm{L\_ce}}{\mathrm{L\_ce\_opt}}+c+1\mathrm{v\_ce}=-\mathrm{Factor}\mathrm{L\_ce}(\frac{(\mathrm{F\_isom}+\mathrm{A\_REL})\mathrm{B\_REL}}{1\frac{F}{\mathrm{F\_max}q}+\mathrm{A\_REL}}-\mathrm{B\_REL})\mathrm{L\_see}=L-\mathrm{L\_ce}c=\frac{-1}{\mathrm{width}^{2}}\mathrm{c2}=\mathrm{F\_isom}\mathrm{F\_asympt}\mathrm{c1}=\frac{\mathrm{Factor}\mathrm{B\_REL}(\mathrm{F\_isom}+\mathrm{c2})^{2}}{(\mathrm{F\_isom}+\mathrm{A\_REL})\mathrm{slope}}\mathrm{c3}=\frac{\mathrm{c1}}{\mathrm{F\_isom}+\mathrm{c2}}L=\begin{cases}1 & \text{if $\mathrm{time}\le 1$}\\ 0.92 & \text{if $(\mathrm{time}> 1)\land (\mathrm{time}< 5)$}\\ 0.9 & \text{otherwise}\end{cases}\frac{d \mathrm{L\_ce}}{d \mathrm{time}}=\mathrm{v\_ce}F=\mathrm{alpha}(\mathrm{L\_see}-\mathrm{L\_slack})$
Harrington
Paul
paul.harrington@auckland.ac.nz
The University of Auckland
Auckland Bioengineering Institute
2010-03-26
skeletal muscle
keyword
mechanical constitutive laws
skeletal muscle
muscle contraction
Nagano
Akinori
Gerritsen
Karin
G
M
Effects of Neuromuscular Strength Training on Vertical Jumping Performance - A Computer Simulation Study
2001
Journal of Applied Biomechanics
17
113
128