Optimized Comfort Fit for Indians: A Machine Learning Based BHA System Study

DOI

10.2991/978-94-6239-616-6_41How to use a DOI?

Keywords

BHA sizing; Footwear; Segmentation; Fitting; Measurement

Abstract

Shoe sizing systems vary significantly around the world, with each country using their own system such as US, UK, European, and Japanese. However, these systems developed internationally have largely been developed based on western foot shapes, and are not a good fit for the unique morphological aspect of Indian foot shapes since Indian feet are typically shorter, wider, and have a higher arch. Thus users in India primarily have issues with shoes that do not fit well, are uncomfortable, and are sized inconsistently across brands. The Bharath (BHA) shoe sizing system was developed as a national standard of shoe sizing that would be inclusive of the population specific shape for shoes based on Indian foot morphology. BHA shoe sizing incorporates foot length, ball girth, heel width and arch height based on Indian samples using sizing utilizing large anthropometric methods and 3D foot scan based sizes. Unlike foreign systems that focus mostly on foot length, the BHA system includes both length and width measurements, making the overall fit more accurate and comfortable for Indian users Furthermore, modern techniques in machine learning and image-driven analysis could also contribute to the automation of foot measurement and the accuracy of predicting BHA size. The BHA system gives India a clear, data-backed way to standardize shoe sizing, improving fit accuracy while opening the door for future digital and AI-based measurement tools.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. Balaji
AU  - R. Elakiya
AU  - P. Deshma
AU  - P. Kaviyalakshmi
PY  - 2026
DA  - 2026/03/31
TI  - Optimized Comfort Fit for Indians: A Machine Learning Based BHA System Study
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 542
EP  - 558
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_41
DO  - 10.2991/978-94-6239-616-6_41
ID  - Balaji2026
ER  -