Back

The effects of muscle fibre type distribution on gait biomechanics: A predictive simulation study

Daehlin, T. E.; Ross, S. A.; De Groote, F.; Wakeling, J. M.

2026-04-15 bioengineering
10.64898/2026.04.13.718234 bioRxiv
Show abstract

AO_SCPLOWBSTRACTC_SCPLOWMuscle fibre type distribution influences both the metabolic and contractile properties of individual muscles. However, as humans tend to self-optimize their gait pattern to minimize cost of transport, these changes in muscle properties may influence gait biomechanics in manners that are difficult to isolate in in vivo experiments. The purpose of this study was to predict the influence of muscle fibre type distribution on the metabolic cost and biomechanics of simulated walking and running. We implemented a muscle model that could predict recruitment of slow and fast twitch muscle fibres in a framework for predictive musculoskeletal simulation. Subsequently, we employed the framework to investigate how metabolic cost of transport, stride length, stride frequency, and mechanical work performed by slow and fast twich muscle fibres were influenced by fibre type distribution across locomotion speeds from 1.0 to 4.5 m {middle dot} s-1. Our results predict that cost of transport increases as slow twitch area fraction decreases, while stride length and frequency was minimally affected by fibre type distribution at speeds resulting in walking. In contrast, fibre type distribution interacts with locomotion speed at speeds resulting in running. Specifically, we predict the existence of a threshold speed below which cost of transport decreases with an increasing proportion of slow twitch fibres, while cost of transport increases with increasing proportions of slow twitch fibres above it. The shift in fibre type distribution was accompanied by an increase in stride frequency and decrease in stride length. These shifts in spatiotemporal characteristics appear to allow the muscles to operate at speeds close to those that achieve peak mechanical efficiency. Taken together, the results of this study predict that muscle fibre type distribution may influence both the energetics and biomechanics of gait, and that this influence is dependent upon the locomotion speed.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Journal of Biomechanics
57 papers in training set
Top 0.1%
18.2%
2
PLOS Computational Biology
1633 papers in training set
Top 2%
14.4%
3
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 0.1%
12.2%
4
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.1%
6.7%
50% of probability mass above
5
Journal of The Royal Society Interface
189 papers in training set
Top 0.6%
6.2%
6
PLOS ONE
4510 papers in training set
Top 37%
3.9%
7
International Journal for Numerical Methods in Biomedical Engineering
12 papers in training set
Top 0.1%
3.6%
8
Annals of Biomedical Engineering
34 papers in training set
Top 0.3%
3.6%
9
PeerJ
261 papers in training set
Top 3%
3.5%
10
Journal of Experimental Biology
249 papers in training set
Top 1%
3.0%
11
Journal of Biomechanical Engineering
17 papers in training set
Top 0.1%
3.0%
12
Journal of NeuroEngineering and Rehabilitation
28 papers in training set
Top 0.4%
2.5%
13
Bioinspiration & Biomimetics
13 papers in training set
Top 0.1%
2.0%
14
Royal Society Open Science
193 papers in training set
Top 2%
1.7%
15
Frontiers in Physiology
93 papers in training set
Top 3%
1.7%
16
Scientific Reports
3102 papers in training set
Top 63%
1.5%
17
Biological Cybernetics
12 papers in training set
Top 0.2%
1.2%
18
Journal of Theoretical Biology
144 papers in training set
Top 1%
0.9%
19
Biology Open
130 papers in training set
Top 3%
0.8%
20
IEEE Transactions on Neural Systems and Rehabilitation Engineering
40 papers in training set
Top 0.7%
0.6%
21
Gait & Posture
22 papers in training set
Top 0.4%
0.6%