Analyzing Body Asymmetry Using 3D Scans and Machine Learning: Insights from Demographic Patterns and Dominant Hand Bias

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 threedimensional 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.