Enhanced Body Composition Estimation from 3D Body Scans

Boyuan Feng, Yijiang Zheng, Ruting Cheng, Shuya Feng, Khashayar Vaziri, James Hahn

2025

Abstract

Accurate body composition assessment is essential for evaluating health and diagnosing conditions like sarcopenia and cardiovascular disease. Approaches for accurately measuring body composition, such as Dual-Energy X-ray Absorptiometry (DXA) and Magnetic Resonance Imaging (MRI), are precise but costly and limited in accessibility. Some studies have explored predicting body composition by using shapes since 3D scanning techniques allow for precise and efficient digital measurements of body shape. This study introduces an enhanced method using 3D body scanning integrated with a part-to-global Multilayer Perceptron (MLP) network that incorporates predefined high-level features for body composition prediction. For lean mass estimation, our method achieved a root mean square error (RMSE) of 2.85 kg. For fat mass estimation, the RMSE was 2.50 kg, and for bone mineral content (BMC), the RMSE was 193.50 g. These results represent substantial improvements over existing methods, highlighting the effectiveness and reliability of our approach in accurately predicting body composition metrics.

Paper Citation

in Harvard Style

Feng B., Zheng Y., Cheng R., Feng S., Vaziri K. and Hahn J. (2025). Enhanced Body Composition Estimation from 3D Body Scans. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOINFORMATICS; ISBN 978-989-758-731-3, SciTePress, pages 421-431. DOI: 10.5220/0013107000003911

in Bibtex Style

@conference{bioinformatics25,
author={Boyuan Feng and Yijiang Zheng and Ruting Cheng and Shuya Feng and Khashayar Vaziri and James Hahn},
title={Enhanced Body Composition Estimation from 3D Body Scans},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOINFORMATICS},
year={2025},
pages={421-431},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013107000003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOINFORMATICS
TI - Enhanced Body Composition Estimation from 3D Body Scans
SN - 978-989-758-731-3
AU - Feng B.
AU - Zheng Y.
AU - Cheng R.
AU - Feng S.
AU - Vaziri K.
AU - Hahn J.
PY - 2025
SP - 421
EP - 431
DO - 10.5220/0013107000003911
PB - SciTePress