Evidence map›Paper›PMID 38446392›Full record

ArticleMedical & biological engineering & computing2024

Custom orthotic design by integrating 3D scanning and subject-specific FE modelling workflow.

Yinghu Peng, Yan Wang, Qida Zhang, Shane Fei Chen, Ming Zhang, Guanglin Li

Abstract read
In one paragraph

Article in Medical & biological engineering & computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Yinghu PengCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Yan WangDepartment of Biomedical Engineering, Faculty of Engineering, Hong Kong Polytechnic University, Hong Kong, 999077, SAR, China.
Qida ZhangMusculoskeletal Research Laboratory, Department of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Hong Kong, SAR, China.
Shane Fei ChenDepartment of Biomedical Engineering, Faculty of Engineering, Hong Kong Polytechnic University, Hong Kong, 999077, SAR, China.
Ming ZhangDepartment of Biomedical Engineering, Faculty of Engineering, Hong Kong Polytechnic University, Hong Kong, 999077, SAR, China. ming.zhang@polyu.edu.hk.
Guanglin LiCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. gl.li@siat.ac.cn.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2022A1515110512Guangdong Science and Technology Department 2022A0505090007Hong Kong Research Grant Council PolyU15211322National Natural Science Foundation of China 11972315
6 · The paper itself

Abstract

The finite element (FE) foot model can help estimate pathomechanics and improve the customized foot orthoses design. However, the procedure of developing FE models can be time-consuming and costly. This study aimed to develop a subject-specific scaled foot modelling workflow for the foot orthoses design based on the scanned foot surface data. Six participants (twelve feet) were collected for the foot finite element modelling. The subject-specific surface-based finite element model (SFEM) was established by incorporating the scanned foot surface and scaled foot bone geometries. The geometric deviations between the scaled and the scanned foot surfaces were calculated. The SFEM model was adopted to predict barefoot and foot-orthosis interface pressures. The averaged distances between the scaled and scanned foot surfaces were 0.23 ± 0.09 mm. There was no significant difference for the hallux, medial forefoot, middle forefoot, midfoot, medial hindfoot, and lateral hindfoot, except for the lateral forefoot region (p = 0.045). The SFEM model evaluated slightly higher foot-orthoses interface pressure values than measured, with a maximum deviation of 7.1%. These results indicated that the SFEM technique could predict the barefoot and foot-orthoses interface pressure, which has the potential to expedite the process of orthotic design and optimization.

Indexed as

Finite Element AnalysisFootImaging, Three-DimensionalPressureAdultBiomechanical PhenomenaEquipment DesignFemaleFoot OrthosesHumansMaleWorkflowYoung AdultCustomized foot scalingFinite element analysisFoot–ankle jointFoot orthosis

Identifiers

PMID38446392
PMCPMC11189969

What OpenQuestion holds

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LicenceCC BY
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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.