Prediction of human male trunk mass distribution using anthropometric measurements: A feasibility study

• Published in: Journal of biomechanics Vol. 122; p. 110437
• Main Authors: Liu, Tao, Khalaf, Kinda, Hebela, Nader, Westover, Lindsey, Galbusera, Fabio, El-Rich, Marwan
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 09.06.2021; Elsevier Limited
• Subjects: Accuracy; Anthropometry; Body height; Body measurements; Bone density; Bones; Cadavers; Conventional neural network; Datasets; Deviation; Error analysis; Feasibility studies; Human body shape; Image acquisition; Image processing; Image segmentation; Males; Mass distribution; Mathematical models; Older people; Principal component analysis; Trunk mass distribution; Trunk mass distribution; Image segmentation; Human body shape; Conventional neural network; Principal component analysis
• ISSN: 0021-9290; 1873-2380; 1873-2380
• DOI: 10.1016/j.jbiomech.2021.110437

The current study proposes a new method to predict the body shape and mass distribution of the trunk (Tl-L5) of a human male using 15 anthropometric measurements acquired at various locations of the body. Trunk cross-sectional images adopted from the Visible Human male project database were segmented into fat, bone, and lean tissue. Assuming that all male subjects have similar cross-sectional composition at a given body height percentile, areas of the segmented cross-sectional images of the Visible Human male along the trunk were scaled to match those of the predicted body shape. The trunk mass distribution of the target subject can then be computed using the density values of fat, bone, and lean tissue. Comparison of the predicted body shape circumference with ground truth values measured using digital and actual measurements yielded maximum mean error of 13.3 mm and 30.3 mm, respectively. The accuracy of the image segmentation was evaluated, and the results showed a high Jaccard index (>0.95). The proposed method was able to predict the trunk mass distribution of two volunteers with a maximum deviation of 384 g at T4 level and a minimum deviation of 12 g at L4 level and the corresponding centers of mass fell within the experimental data at most levels. Thus, our method can be considered as a feasible option to calculate subject-specific trunk mass distribution.