Authors:

Steven C. HAUSER, Matthew S. GILMER, David BRUNER, Breck SIEGLINGER

Size Stream LLC, Cary NC, USA

DOI:

https://doi.org/10.15221/24.09

Full paper:

PDF

Keywords:

3D body scanning, machine learning, mobile scanning, body fat measurement, body composition

Abstract:

Advancements in mobile technology and artificial intelligence have transformed body composition assessment, providing a practical alternative to traditional methods like air displacement plethysmography (ADP), dual energy X-ray absorptiometry (DXA), and expensive optical booth scanners for 3D body measurement. This paper evaluates the competitiveness of Size Stream's mobile 3D body scanning applications against these alternatives and compares their performance with two-point and four-point bioimpedance devices. Based on a substantial dataset of 209 samples across 118 subjects, body composition was assessed using a four-compartment model, incorporating DXA, bioimpedance analysis, body volume measurements, and body weight. Our findings demonstrate that mobile device 3D scanning achieves impressive accuracy and reliability, closely aligning with full booth results and outperforming conventional bioimpedance scales. The paper details the methodology, data analysis, and comparative metrics, highlighting the potential of mobile devices as viable tools for body composition assessment. This advancement not only enhances accessibility but also ensures precision and accuracy in health and fitness applications.

How to Cite (MLA):

Hauser, Steven C. et al., "Advancements in Body Composition Assessment using Mobile Devices", 3DBODY.TECH Journal, vol. 1, Oct. 2024, #09, https://doi.org/10.15221/24.09.

Presentation:

VIDEO availble in proceedings

Details:

Volume/Issue: 3DBODY.TECH Journal - Vol. 1, 2024
Paper: #09
Published: 2024/10/30
Presented at: 3DBODY.TECH 2024, 22-23 Oct. 2024, Lugano, Switzerland
Proceedings: 3DBODY.TECH 2024 Proceedings

License/Copyright notice

Copyright © 2024 by the author(s).
This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The papers appearing in the journal reflect the author's opinions. Their inclusion in the volumes does not necessary constitute endorsement by the editor or by the publisher.

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