Cited by 24Sports Performance and TrainingLower Extremity Biomechanics and PathologiesCardiovascular and exercise physiology

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index; 1 of the 26 sources its claims cite were checked for support.

Update and extension of the ‘Equivalent Slope’ of speed changing level locomotion in humans: a computational model for shuttle running

Open access
Minetti, Alberto E., Pavei, Gaspare·2018·Journal of Experimental Biology

Abstract

Controlled experimental protocols for metabolic cost assessment of speed-changing locomotion are quite complex to design and manage. The use of the ‘equivalent slope’, i.e. the gradient locomotion at constant speed metabolically equivalent to a level progression in acceleration, has proved valuable in the estimation of the metabolic cost of speed-changing gaits. However, its use with steep slopes requires extrapolation of the experimental cost versus gradient function for constant running speed, resulting in less-reliable estimates. The present study extended the model to also work with deceleration, and revised the predictive equation to enable it to be applied to much higher levels of speed change. Shuttle running at different distances (from 5+5 to 20+20 m) was then investigated using the novel approach and software, and the predictions in terms of metabolic cost and efficiency compare well with the experimental data.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The paper updates and extends the “equivalent slope” model to include deceleration and higher speed changes, providing computational equations for the metabolic cost of accelerated and decelerated running. It applies the model to shuttle running from 5+5 to 20+20 m, where predicted metabolic cost and apparent efficiency compare well with experimental data.

Key findings

  • New gradient-running cost equations were fitted: uphill \(C_{PG}=39.5i+3.6e^{-4i}\) and downhill \(C_{NG}=-8.34i+3.6e^{13i}\); in the range \(-0.45\le i\le +0.45\), the ratio of these to the previous Eqn 1 averaged 0.9993.
  • The extended equivalent-slope model gives \(C_{AR}=0.102(a_f^2+96.2)^{0.5}(4.03a_f+3.6e^{-0.408a_f})\) for \(0<a_f<8.24\) m s\(^{-2}\), and \(C_{DR}=0.102(d_f^2+96.2)^{0.5}(-0.85d_f+3.6e^{1.33d_f})\) for \(-4.41<d_f<0\) m s\(^{-2}\), with suggested safe extension to \(-8.24<d_f<0\) m s\(^{-2}\).
  • The shuttle-run model overestimated measured maximum speed by 4.96±1.64%; predicted average apparent efficiency of positive work was 35.3%, 29.9%, 23.2% and 17.5% for 20+20, 15+15, 10+10 and 5+5 m shuttles, respectively.
  • Sprinting required about 1 J kg\(^{-1}\) m\(^{-1}\) more internal work than uphill running at the same equivalent slope/slope (0.925±0.069 J kg\(^{-1}\) m\(^{-1}\)), corresponding to \(C_{extraWint}=3.083\) J kg\(^{-1}\) m\(^{-1}\) at a muscle efficiency of 0.30.

Methods

  • The mathematical model pooled prior gradient-running cost data (Minetti et al., 2002; Giovanelli et al., 2016) to fit new uphill and downhill cost equations, then combined equivalent slope and equivalent mass to derive equations for accelerated and decelerated running.
  • The shuttle-running computational model assumed mono-exponential speed changes, \(v=v_{max}(1-e^{-t/\tau})\), with inputs from maximal 20+20 m shuttle-run kinematics: \(v_{max}=7.175\) m s\(^{-1}\), \(\tau_{af}=0.803\) s\(^{-1}\), \(\tau_{df}=0.472\) s\(^{-1}\) (CV 7.7–10.9%); an iterative process found the maximum speed and average metabolic cost for each shuttle distance.
  • Predictions were compared with experimental shuttle-running metabolic cost from Buglione and di Prampero (2013) and Zamparo et al. (2015), with apparent efficiency compared with unpublished shuttle-run data and internal work compared between 20 m sprinting and uphill treadmill running.

Limitations

  • The paper states that extrapolation of the earlier Eqn 8 at very high slopes is improved by Eqns 9 and 11, but the lower deceleration limit (\(-8.24\) m s\(^{-2}\)) is not close to human maximum; downhill metabolic data are lacking below \(i<-0.45\), and measurements should be extended to about \(-143\%\) slope.
  • The paper states that approximations in the mathematical and computational model can affect predictions, including the asymptotic trend for steep downhill slopes and the assumption that short shuttle runs use truncated portions of long-run acceleration/deceleration, which generates a sharp speed peak slightly different from experimental patterns.
  • The paper states that the model does not include all potential metabolic costs, such as isometric contractions and stabilizing co-contractions; turning cost is estimated but other components are not, and internal-work bias may arise because gradient running and sprint/shuttle running involve different stride frequencies and speeds. Evident from the text: predictions rely partly on unpublished shuttle-run kinematic data and comparisons to unpublished data, and no new experimental metabolic measurements were collected in this study.

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Integrity signals

Registry

Crossref · 10.1242/jeb.182303

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

15 Own interpretation · 13 No full text of the sources · 12 No basis given · 5 Own result · 3 Not checked yet · 3 Own method · 2 Sources not found · 1 Partly supported · accuracy not yet measured

Verify all 1 references — free account

Show all 35 claims

  • It may state two separate claims as one. 11
  • Probably not a substantial claim. 9
19 of 19
  • The authors state this as an assumption.

    The accelerative and decelerative phases of a maximal shuttle run of different section distances are portions of the same patterns exhibited when performing a very long shuttle run (20+20 m).

    “The model is based on the assumption that the accelerative and decelerative phases of a maximal shuttle run (SR) of different section (leg) distances are portions of the same patterns exhibited when performing a very long SR (say 20+20 m).”
  • The authors state this as an assumption.

    The apparent efficiency of positive mechanical work as a function of slope is: 0 for downhill slopes steeper than -0.35; increasing up to 0.80 at i=0; decreasing down to 0.25 at +0.35; and constant 0.25 beyond +0.35.

    “Therefore, with respect to the slope, the apparent efficiency of positive mechanical work is assumed to be: (a) 0 for downhill slopes steeper than -0.35,(b) an increasing value up to 0.80 at i=0 (in that range and in the next, different mixes of positive and negative work are performed), which is the maximum apparent efficiency of positive muscle work in level running at the maximum speed of SRs (”
  • The authors state this as an assumption.

    The average apparent efficiency of positive work along one shuttle-run leg is the same for the other leg(s).

    “From the calculated average value along one SR leg [eff mean , assumed to be the same for the other leg(s)], we could infer how much mechanical energy saving via the elastic mechanism has occurred (zero for eff mean ≈0.25 and the maximum possible when approaching 0.75-0.80).”
  • The authors state this as an assumption.

    Short-distance SRs use 'truncated' portions of acceleration and deceleration phases displayed at the maximum investigated distance.

    “the assumption ruling the simulation, i.e. that short-distance SRs use 'truncated' portions of acceleration and deceleration phases displayed at the maximum investigated distance”
4 of 4

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

4 of 4

Citations

Cites

Show all 28 references

Research works printed but not linked: 1

  1. Margaria, 1938, Sulla fisiologia e specialmente sul consumo energetico della marcia e della corsa a varia velocità ed inclinazione del terreno, Atti Acc. Naz. Lincei, 6, 299

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Metadata

Authors
Minetti, A. E., & Pavei, G.
Affiliations
University of Milan (IT)
Corresponding author
Minetti, Alberto E.
Venue
Journal of Experimental Biology
Published
2018-01-01
Volume
221
Issue
Pt 15
ISSN
  • 0022-0949 (ISSN-L)
  • 1477-9145
OpenAlex
W2808359881
Cited by
24
References
28
Citations by year
2026: 1 · 2025: 3 · 2024: 3 · 2023: 4 · 2021: 3 · 2020: 6 · 2019: 2 · 2018: 2
FWCI
3.58
Type
journal article
Language
en
Open access
Locations
  • Journal of Experimental Biology (publishedVersion)
  • PubMed (publishedVersion)
  • Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
  • HighWire Press Open Archive (submittedVersion)
Topics
  • Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
  • Physical Sciences › Engineering › Biomedical Engineering › Lower Extremity Biomechanics and Pathologies
  • Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
Keywords
shuttle run, metabolic cost, energy expenditure, computational model, deceleration, acceleration, running efficiency, human locomotion
MeSH terms
Acceleration, Energy Metabolism, Humans, Models, Theoretical, Running

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