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Record W2004467364 · doi:10.15221/14.192

A Low Cost 3D Scanning and Printing Tool for Clinical Use in the Casting and Manufacture of Custom Foot Orthoses

2014· article· en· W2004467364 on OpenAlexaff
Colin E. Dombroski, Megan E. R. Balsdon, Adam Froats

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsWestern University
Fundersnot available
Keywords3D printingCasting3d scanning3d printedFoot (prosody)Computer scienceEngineering drawingMaterials scienceEngineeringManufacturing engineeringMechanical engineeringComposite materialArtificial intelligenceArt

Abstract

fetched live from OpenAlex

Custom foot orthoses are currently recognized as the gold standard for treatment of foot and lower limb pathology. Applications include, but are not limited to: pain relief, increased heel cushion, correction of flexible deformity, increased foot stability and/or prevention of skin breakdowns, such as ulceration. While foam and plaster casting methods are most widely used for the fabrication of custom foot orthoses, technology has emerged, permitting the use of 3D scanning, computer aided design (CAD) and computer aided manufacturing (CAM) for fabrication of foot molds and custom foot orthotic components. Adoption of 3D printing, as a form of CAM, requires further investigation for use as a clinical tool. This study provides a preliminary description of a new method to manufacture foot orthoses using a novel 3D scanner and printer and compare gait kinematic outputs from shod and traditional plaster casted orthotics. One participant (male, 25 years) was included with no lower extremity injuries. Foot molds were created from 3D scanning and printing methods, using the Microsoft Kinect scanning device and desktop Makerbot printer, respectively. Foot molds were also created from the traditional plaster casting method. Custom foot orthoses were then fabricated from each positive foot mold. Lower body plug-in-gait with the Oxford Foot Model (OFM) on the right foot was collected for the 3D printing orthotic, plaster casted orthotic and control (shod) conditions. The medial longitudinal arch (MLA) was measured using an arch height index (AHI) measurement extracted from the OFM outputs, where a decrease in AHI represented a drop in arch height. The lowest AHI was 21.2 mm in the running shoes, followed by 21.4 mm wearing the orthoses made using 3D scanning and printing, with the highest AHI of 22.0 mm while the participant wore the plaster casted orthoses. This preliminary study demonstrated a small increase in AHI with the 3D printing orthotic compared to the shod condition, indicating that the orthotic restricted motion of the MLA during midstance. A larger sample size may demonstrate significant patterns for the tested conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.292
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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