Predicting joint loading in Asian overweight and obese females with flexible flatfoot: a regression analysis of anthropometric parameters and gait dynamics.

Linjuan Wei, Guoxin Zhang, Tony Lin-Wei Chen, Yan Wang, Yinghu Peng, Ming Zhang

Abstract read

In one paragraph

Article in Medical & biological engineering & computing, 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

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

1 citing paper in PubMed.

Effects of excess bodyweight and flexible Flatfoot on female stance-phase lower-limb biomechanics assessed by statistical non-parametric mapping.Scientific reports · 2025
Article

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

6 authors.

Linjuan WeiDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, 999077, China.

Guoxin ZhangDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, 999077, China.

Tony Lin-Wei ChenDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, 999077, China.

Yan WangDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, 999077, China.

Yinghu PengInstitutes of Advanced Technology, CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Chinese Academy of Sciences, Shenzhen, 518055, China.

Ming ZhangDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, 999077, China. ming.zhang@polyu.edu.hk.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2022A1515110512the Research Grants Council RGC 15211322

6 · The paper itself

Abstract

Current methods for obtaining accurate joint loading data lack simplicity, efficiency, and cost-effectiveness. This study aims to generate joint loading prediction models using anthropometric parameters and walking speed in overweight or obese females with flexible flatfoot. Sixteen participants' motion capture data from walking trails and anthropometric parameters were collected. The lower limb joint contact forces and the walking speed were calculated via a musculoskeletal model. Regression analysis was used to generate the prediction model. The second peak of knee joint contact force revealed a strong negative correlation with hip circumference and a weak positive correlation with age (p < 0.001 and adjusted R

Indexed as

FlatfootGaitObesityOverweightAdultAnkle JointAnthropometryAsian PeopleBiomechanical PhenomenaFemaleHumansKnee JointMiddle AgedRegression AnalysisWalking SpeedWeight-BearingAnthropometricsFlexible flatfootKineticsRegression analysis

Identifiers

PMID40490675

DOI10.1007/s11517-025-03378-y

PMCPMC12634799

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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.