Evidence map›Paper›PMID 41133614›Full record

ArticleMuscles (Basel, Switzerland)2025

Guidelines for Sport Compressive Garments Design: Finite Element Simulations Approach.

Alessandro Cudicio, Marta Cogliati, Gianluca Rizzi

Abstract read
In one paragraph

Article in Muscles (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

3 authors.

Alessandro CudicioDepartment of Human and Social Sciences, University of Bergamo, 24129 Bergamo, Italy.ORCID 0000-0003-1891-3812
Marta CogliatiDepartment of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy.ORCID 0000-0002-3836-2635
Gianluca RizziChair of Continuum Mechanics, Faculty of Architecture and Civil Engineering, TU-Dortmund, August-Schmidt-Str. 8, 44227 Dortmund, Germany.ORCID 0000-0002-5967-5403

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDespite significant attention being paid to compression garments (CG) in the sports field, there remains ongoing debate regarding their actual effectiveness in enhancing athletic performance and expediting post-exercise recovery. This article examines their various aspects, with a focus on CG design and the materials they are made of, aiming to analyze the importance of personalized compression strategies based on individual anthropometric measurements and non-linear compression designs.

methodsUsing anthropometric analysis of 40 healthy participants, this study examines the morphological characteristics of the lower limb and their implications for CG design.

resultsMeasurements of limb length and circumferences revealed complex interactions among anatomical variables, emphasizing the need for customized and adaptable device design. Finite element simulations clarified the challenges in achieving uniform pressure gradients along the lower limb, highlighting the limitations of one-piece devices and suggesting tailored segmented designs for individual limb segments.

conclusionThe results demonstrate that one-piece devices often fail to provide optimal compression due to non-linear variations in limb dimensions. Conversely, segmented devices, particularly those with bilinear progression, exhibited superior performance in applying targeted compression across different limb segments. This more detailed approach to customization could significantly contribute to optimizing outcomes and user comfort.

Indexed as

compressive garmentscustomized garment designfinite element simulationgraduated compressionsport garmentsport performance

Identifiers

PMID41133614
PMCPMC12550921

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Registered trials

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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.