Evidence map›Paper›PMID 40096386›Full record

ArticleSensors (Basel, Switzerland)2025

Measurement of Human Body Segment Properties Using Low-Cost RGB-D Cameras.

Cristina Nuzzi, Marco Ghidelli, Alessandro Luchetti, Matteo Zanetti, Francesco Crenna, Matteo Lancini

Abstract read
In one paragraph

Article in Sensors (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

6 authors.

Cristina NuzziDepartment of Mechanical and Industrial Engineering (DIMI), University of Brescia, Via Branze 38, 25123 Brescia, Italy.ORCID 0000-0001-5530-6136
Marco GhidelliDepartment of Medical and Surgical Specialties, Radiological Sciences, and Public Health (DSMC), University of Brescia, Viale Europa 11, 25123 Brescia, Italy.ORCID 0000-0001-5607-7574
Alessandro LuchettiDepartment of Industrial Engineering (DII), University of Trento, Via Sommarive 9, 38123 Trento, Italy.ORCID 0000-0003-0960-0996
Matteo ZanettiDepartment of Industrial Engineering (DII), University of Trento, Via Sommarive 9, 38123 Trento, Italy.ORCID 0000-0002-8813-215X
Francesco CrennaDepartment of Mechanical Engineering, Energetics, Management and Transportation (DIME), University of Genova, Via alla Opera Pia 15, 16145 Genova, Italy.ORCID 0000-0002-4803-2082
Matteo LanciniDepartment of Medical and Surgical Specialties, Radiological Sciences, and Public Health (DSMC), University of Brescia, Viale Europa 11, 25123 Brescia, Italy.ORCID 0000-0002-2301-876X

Funding

Horizon 2020 research and innovation programme, Project "EUROBENCH" 779963
6 · The paper itself

Abstract

An open question for the biomechanical research community is accurate estimation of the volume and mass of each body segment of the human body, especially when indirect measurements are based on biomechanical modeling. Traditional methods involve the adoption of anthropometric tables, which describe only the average human shape, or manual measurements, which are time-consuming and depend on the operator. We propose a novel method based on the acquisition of a 3D scan of a subject's body, which is obtained using a consumer-end RGB-D camera. The body segments' separation is obtained by combining the body skeleton estimation of BlazePose with a biomechanical-coherent skeletal model, which is defined according to the literature. The volume of each body segment is computed using a 3D Monte Carlo procedure. Results were compared with manual measurement by experts, anthropometric tables, and a model leveraging truncated cone approximations, showing good adherence to reference data with minimal differences (ranging from +0.5 to -1.0 dm

Indexed as

AnthropometryImaging, Three-DimensionalAdultBiomechanical PhenomenaFemaleHumansMaleMonte Carlo Methodanthropometrybiomechanicsbody segment parametersbody volume estimationKinect Azuremeasurement science

Identifiers

PMID40096386
PMCPMC11902671

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.