Influence of central and peripheral motor unit properties on isometric muscle force entropy: A computer simulation study

Jakob Dideriksen*, Leonardo Abdala Elias, Ellen Pereira Zambalde, Carina Marconi Germer, Ricardo Gonçalves Molinari, Francesco Negro

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)
21 Downloads (Pure)


Approximate entropy of isometric force is a popular measure to characterize behavioral changes across muscle contraction conditions. The degree to which force entropy characterizes the randomness of the motor control strategy, however, is not known. In this study, we used a computational model to investigate the correlation between approximate entropy of the synaptic input to a motor neuron pool, the neural drive to muscle (cumulative spike train; CST), and the force. This comparison was made across several simulation conditions, that included different synaptic command signal bandwidths, motor neuron pool sizes, and muscle contractile properties. The results indicated that although force entropy to some degree reflects the entropy of the synaptic command to motor neurons, it is biased by changes in motor unit properties. As a consequence, there was a low correlation between approximate entropy of force and the motor neuron input signal across all simulation conditions (r2 = 0.13). Therefore, force entropy should only be used to compare motor control strategies across conditions where motor neuron properties can be assumed to be maintained. Instead, we recommend that the entropy of the descending motor commands should be estimated from CSTs comprising spike trains of multiple motor units.

Original languageEnglish
Article number110866
JournalJournal of Biomechanics
Publication statusPublished - Jun 2022

Bibliographical note

Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.


  • Force variability
  • Approximate entropy
  • Neural drive
  • Computational model


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