Evidence map›Paper›PMID 40014596›Full record

ArticlePloS one2025

Estimation of maximum lower limb muscle strength from vertical jumps.

Chuan-Fang Hou, Chin-Wei Hsu, Philip X Fuchs, Tzyy-Yuang Shiang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chuan-Fang HouDepartment of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei, Taiwan.
Chin-Wei HsuDepartment of Sport and Kinesiology, National Taiwan Normal University, Taipei, Taiwan.
Philip X FuchsDepartment of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei, Taiwan.ORCID 0000-0002-7463-8301
Tzyy-Yuang ShiangDepartment of Sport and Kinesiology, National Taiwan Normal University, Taipei, Taiwan.ORCID 0000-0002-1641-3091

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Determining the one-repetition maximum (1RM) is crucial for organizing training loads, but it also is time-consuming, physically demanding, and poses a risk of injury. Vertical jumps are a less demanding and well-established method to test the ability of the lower limbs to generate great forces over a short time, which may allow for the estimation of 1RM in squatting. The purpose of this study was to develop a model for estimating 1RM back squat from ground reaction forces during vertical jumps. Thirteen healthy participants completed a 1RM back squat test, countermovement jumps, and squat jumps. Five kinematic and kinetic variables (e.g., peak and mean power, relative net impulse, jump height, and peak kinetic energy during various phases) were derived from ground reaction forces collected via a Kistler force plate (1000 Hz). Five out of 5 variables correlated with 1RM in countermovement jump and squat jump (ICC = .96-.98, r = .88-.95, p < .001 and ICC = .97-.99, r = .76-.90, p < .05, respectively). The most accurate stepwise regression model (adjusted R2 = .90, SEE =  13.24 kg, mean error =  7.4% of mean 1RMm, p < .001) estimated 1RM back squat based on peak kinetic energy during countermovement jumps. Estimation errors ranged from 7.4% to 10.7% of mean measured 1RM, with no differences between estimated and measured values (d <  0.01, p = .96-1.00). Estimating 1RM via jump tests may offer a practical alternative to traditional methods, reducing injury risks, testing intervals, and effort. Our study proposes a new possible approach for estimating 1RM back squat from jump forces, providing coaches and sports professionals with a more efficient tool to monitor and adjust training loads.

Indexed as

Lower ExtremityMuscle, SkeletalMuscle StrengthAdultBiomechanical PhenomenaExercise TestFemaleHumansMaleYoung Adult

Identifiers

PMID40014596
PMCPMC11867321

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LicenceCC BY
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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.