Evidence map›Paper›PMID 42676987›Full record

ArticleData in brief2026

Design and manufacturing data for an infant upper body physical model for bench testing of assistive devices.

Emily Kuo, Chris Rauch, Christian Macaluso, Aryan Gowda, Jonathan Ortega, Miriam Contreras Castillo, Melanie Barahona, Tristan McCarty, Ipsita Sahin, Elena Kokkoni

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Data in brief, 2026. 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

10 authors.

Emily KuoDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Chris RauchDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Christian MacalusoDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Aryan GowdaDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Jonathan OrtegaDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Miriam Contreras CastilloDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Melanie BarahonaDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Tristan McCartyDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Ipsita SahinDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.
Elena KokkoniDepartment of Bioengineering, University of California, 900 University Ave, Riverside, CA 92521-0001, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pediatric assistive devices require rigorous preliminary testing for safety and effectiveness before conducting trials with pediatric populations. Existing upper-body physical models for infants are often prohibitively expensive; meanwhile, more affordable alternatives frequently lack anthropometric accuracy or adequate joint mobility. This paper presents design and manufacturing data for a high-fidelity model that closely mirrors the physical properties of a six-month-old infant's upper body. A comprehensive guide to the design process, manufacturing, and assembly is also included. The model consists of the torso, upper arms, forearms, and hands, connected with articulated joints. Validation of the model's segments confirms close alignment with target metrics for size, mass distribution, and joint mobility. By adjusting the design parameters, the infant model can be scaled to represent older pediatric populations. This work offers a scalable framework for researchers to develop physical models for pediatric device testing.

Indexed as

Additive manufacturingComputer-aided designManikin

Identifiers

PMID42676987
PMCPMC13527506

What OpenQuestion holds

Textmetadata
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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.