Computational model to investigate the relative contributions of different neuromuscular properties of tibialis anterior on force generated during ankle dorsiflexion

Siddiqi, A, Poosapadi Arjunan, S and Kumar, D 2018, 'Computational model to investigate the relative contributions of different neuromuscular properties of tibialis anterior on force generated during ankle dorsiflexion', Medical and Biological Engineering and Computing, vol. 56, no. 8, pp. 1413-1423.


Document type: Journal Article
Collection: Journal Articles

Title Computational model to investigate the relative contributions of different neuromuscular properties of tibialis anterior on force generated during ankle dorsiflexion
Author(s) Siddiqi, A
Poosapadi Arjunan, S
Kumar, D
Year 2018
Journal name Medical and Biological Engineering and Computing
Volume number 56
Issue number 8
Start page 1413
End page 1423
Total pages 11
Publisher Springer
Abstract This study describes a new model of the force generated by tibialis anterior muscle with three new features: single-fiber action potential, twitch force, and pennation angle. This model was used to investigate the relative effects and interaction of ten age-associated neuromuscular parameters. Regression analysis (significance level of 0.05) between the neuromuscular properties and corresponding simulated force produced at the footplate was performed. Standardized slope coefficients were computed to rank the effect of the parameters. The results show that reduction in the average firing rate is the reason for the sharp decline in the force and other factors, such as number of muscle fibers, specific force, pennation angle, and innervation ratio. The fast fiber ratio affects the simulated force through two significant interactions. This study has ranked the individual contributions of the neuromuscular factors to muscle strength decline of the TA and identified firing rate decline as the biggest cause followed by decrease in muscle fiber number and specific force. The strategy for strength preservation for the elderly should focus on improving firing rate.
Subject Rehabilitation Engineering
Biomedical Engineering not elsewhere classified
Signal Processing
Keyword(s) Age
Force
Modeling
Muscle
DOI - identifier 10.1007/s11517-018-1788-1
Copyright notice © International Federation for Medical and Biological Engineering 2018
ISSN 0140-0118
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