Analyzing Body Asymmetry Using 3D Scans and Machine Learning: Insights from Demographic Patterns and Dominant Hand Bias - 25.30
Title:
Analyzing Body Asymmetry Using 3D Scans and Machine Learning: Insights from Demographic Patterns and Dominant Hand Bias
Authors:
Yingying WU 1, Kristen MORRIS 2, Xuebo LIU 1, Reannan BOISVERT 1, Hongyu WU 1
1 Kansas State University, Manhattan, KS, USA;
2 Colorado State University, Fort Collins, CO, USA
Keywords:
3D body scanning, body asymmetry, machine learning
Abstract:
Accurate body measurements underpin anthropometry, ergonomics, and apparel design, yet practitioners often assume bilateral symmetry and measure only one side. The rationale for this convention is limited. Therefore, this exploratory study aimed at quantifying body asymmetries at various body locations for improving the accuracy of measurement protocols, garment patterns, and ultimately product fit. The researchers analyzed 22 paired measurements derived from three-dimensional body scans of 245 adults. Statistical tests included independent samples t-tests, Pearson correlations, and chi-square tests. The researchers further applied a Support Vector Machine model to examine relationships between asymmetry, demographics, and hand dominance. The results reveal where asymmetries are negligible versus practically meaningful, highlight relationships among body dimensions, and identify demographic and dominance factors associated with asymmetry. Based on these findings, the researchers propose actionable recommendations for refining anthropometric procedures and patternmaking standards, encouraging when bilateral measurements are warranted and when single-side measures suffice.
Full paper:
Note:
This paper is currently under review for publication in the 3DBDOY.TECH Journal - Vol. 2, 2025 (jrnl.3dbody.tech).
It will be updated also in this page once the review process is concluded.
Presentation:
VIDEO will be available here in Q3.2026.
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How to Cite (MLA):
Y. Wu et al., "Analyzing Body Asymmetry Using 3D Scans and Machine Learning: Insights from Demographic Patterns and Dominant Hand Bias", Proceedings of 3DBODY.TECH 2025 - 16th International Conference and Expo on 3D/4D Body Scanning, Data and Processing Technologies, Lugano, Switzerland, 21-22 Oct. 2025, #30, https://doi.org/10.15221/25.30
Details:
Proceedings: 3DBODY.TECH 2025, 21-22 Oct. 2025, Lugano, Switzerland
Paper/Presentation: #30
DOI: https://doi.org/10.15221/25.30
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