Evidence map›Paper›PMID 36710857›Full record

ArticlePeerJ2023

Musculoskeletal simulations to examine the effects of accentuated eccentric loading (AEL) on jump height.

Eric Yung-Sheng Su, Timothy J Carroll, Dominic J Farris, Glen A Lichtwark

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Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Eric Yung-Sheng SuSchool of Human Movement and Nutrition Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
Timothy J CarrollSchool of Human Movement and Nutrition Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
Dominic J FarrisSchool of Human Movement and Nutrition Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
Glen A LichtwarkSchool of Human Movement and Nutrition Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: During counter movement jumps, adding weight in the eccentric phase and then suddenly releasing this weight during the concentric phase, known as accentuated eccentric loading (AEL), has been suggested to immediately improve jumping performance. The level of evidence for the positive effects of AEL remains weak, with conflicting evidence over the effectiveness in enhancing performance. Therefore, we proposed to theoretically explore the influence of implementing AEL during constrained vertical jumping using computer modelling and simulation and examined whether the proposed mechanism of enhanced power, increased elastic energy storage and return, could enhance work and power. Methods: We used a simplified model, consisting of a ball-shaped body (head, arm, and trunk), two lower limb segments (thigh and shank), and four muscles, to simulate the mechanisms of AEL. We adjusted the key activation parameters of the muscles to influence the performance outcome of the model. Numerical optimization was applied to search the optimal solution for the model. We implemented AEL and non-AEL conditions in the model to compare the simulated data between conditions. Results: Our model predicted that the optimal jumping performance was achieved when the model utilized the whole joint range. However, there was no difference in jumping performance in AEL and non-AEL conditions because the model began its push-off at the similar state (posture, fiber length, fiber velocity, fiber force, tendon length, and the same activation level). Therefore, the optimal solution predicted by the model was primarily driven by intrinsic muscle dynamics (force-length-velocity relationship), and this coupled with the similar model state at the start of the push-off, resulting in similar push-off performance across all conditions. There was also no evidence of additional tendon-loading effect in AEL conditions compared to non-AEL condition. Discussion: Our simplified simulations did not show improved jump performance with AEL, contrasting with experimental studies. The reduced model demonstrates that increased energy storage from the additional mass alone is not sufficient to induce increased performance and that other factors like differences in activation strategies or movement paths are more likely to contribute to enhanced performance.

Indexed as

Muscle, SkeletalTendonsLower ExtremityMovementPostureAccentuated eccentric loadingBiomechanicsComputer simulationExercise trainingMusculoskeletal modellingOpenSimSports performanceSports science

Identifiers

PMID36710857
PMCPMC9879160

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.