Predicting Body Size and Shape for Vietnamese Males Using Fuzzy Logic

Predicting Body Size and Shape for Vietnamese Males Using Fuzzy Logic

  IJETT-book-cover           
  
© 2025 by IJETT Journal
Volume-73 Issue-5
Year of Publication : 2025
Author : Mong Hien Thi Nguyen, Minh Dương Nguyen, Mau Tung Nguyen
DOI : 10.14445/22315381/IJETT-V73I5P122

How to Cite?
Mong Hien Thi Nguyen, Minh Dương Nguyen, Mau Tung Nguyen, "Predicting Body Size and Shape for Vietnamese Males Using Fuzzy Logic," International Journal of Engineering Trends and Technology, vol. 73, no. 5, pp.256-266, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I5P122

Abstract
The paper presents results of establishing a predictive model for body size and shape for Vietnamese males living in the Southern region. The study surveyed measurements on 353 men aged 18 to 60. They live in Southern Vietnam. The methods of principal component analysis, K-Mean cluster analysis, discriminant analysis, and ANOVA testing using SPSS software have identified six distinct body shape groups. The methods create objective functions that support the development of a sizing chart for Vietnamese males. The fuzzy logic technique is used to predict body size and shape. The feasibility of the predictive model was tested and evaluated on a sample of 30 men within the research age range. Results matched the sizes and body shapes of the test subjects. The predictive model for determining body size and shape using fuzzy logic techniques opens a new direction for the role of AI in modern fashion design and production. With a sizing system table that has many sizes, extracting the size will take a lot of time. This model will help customers minimize the time needed to determine their physical measurements and body shape. From there, they can make decisions on selecting appropriate clothing sizes and patterns when ordering custom-made garments or purchasing ready-made products, whether directly or through online sales channels.

Keywords
Body shape, Body size, Fuzzy logic, Fuzzy set, Sizing system table.

References
[1] Lichuan Wang et al., “Intelligent Fashion Recommender System: Fuzzy Logic in Personalized Garment Design,” IEEE Transactions on Human-Machine Systems, vol. 45, no. 1, pp. 95-109, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Zhujun Wang et al., “A Knowledge-Supported Approach for Garment Pattern Design Using Fuzzy Logic and Artificial Neural Networks,” Multimedia Tools and Applications, vol. 81, pp. 19013-19033, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Joy Sarkar, Md Abdullah Al Faruque, and Elias Khalil, “Predicting the Tearing Strength of Laser Engraved Denim Garments Using a Fuzzy Logic Approach,” Heliyon, vol. 8, no. 1, pp. 1-9, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Imran Hassan, and Suman Kar, “The Application of Fuzzy Logic Techniques to Improve Decision Making in Apparel Size,” World Journal of Advanced Research and Reviews, vol. 19, no. 2, pp. 607-615, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Temesgen Agazhie, and Shalemu Sharew Hailemariam, “Application of Fuzzy Failure Mode and Effect Analysis to Investigate Lean Wastes in the Sewing Section,” International Journal of Quality & Reliability Management, vol. 41, no. 10, pp. 2505-2525, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Adepeju Abimbola Opaleye, Adekunle Kolawole, and Oliver Ekepre Charles-Owaba, “Application of Fuzzy Clustering Methodology for Garment Sizing,” American Journal of Data Mining and Knowledge Discovery, vol. 4, no. 1, pp. 24-31, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Thouraya Hamdi, Adel Ghith, and F. Fayala, “Fuzzy Logic Method for Predicting the Effect of Main Fabric Parameters Influencing Drape Phenomenon,” Autex Research Journal, vol. 20, no. 3, pp. 220-227, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Anirban Dutta, Biswapati Chatterjee, and Syed Kanchan, “Study on Relationships Between Objective and Subjective Evaluation of Drapeability and the Prediction of Subjective Rating of Drapeability Through Fuzzy Logic in Case of Shirting Fabric,” International Journal for Modern Trends in Science and Technology, vol. 6 no. 9, pp. 72-77, 2020.
[Google Scholar]
[9] Kaixuan Liu et al., “An Evaluation of Garment Fit to Improve Customer Body Fit of Fashion Design Clothing,” The International Journal of Advanced Manufacturing Technology, vol. 120, pp. 2685-2699, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Berihun Bizuneh, Abrham Destaw, and Bizuayehu Mamo, “Analysis of Garment Fit Satisfaction and Fit Preferences of Ethiopian Male Consumers,” Research Journal of Textile and Apparel, vol. 27, no 2, pp. 228-245, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Berihun Bizuneh et al., “Garment Sizing System Development for Amhara Policemen Uniforms using Data Mining Techniques,” Research Journal of Textile and Apparel, vol. 29, no. 1, pp. 61-80, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Kaixuan Liu et al., “Fuzzy Classification of Young Women's Lower Body Based on Anthropometric Measurement,” International Journal of Industrial Ergonomics, vol. 55, pp. 60-68, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Evrim Buyukaslan, Fatma Baytar, and Fatma Kalaoglu, “Exploring the Factors Influencing Consumers’ Virtual Garment Fit Satisfactions,” Research Journal of Textile and Apparel, vol. 24, no. 4, pp. 375-388, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Marzena Malara et al., “Body Shape Index versus Body Mass Index as Correlates of Health Risk in Young Healthy Sedentary Men,” Journal of Translational Medicine, vol. 13, no. 1, pp. 1-5, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Martina Gažarová, Mária Galšneiderová, and Lucia Mečiarová, “Obesity Diagnosis and Mortality Risk Based on a Body Shape Index (ABSI) and Other Indices and Anthropometric Parameters in University Students,” Annals of the National Institute of Hygiene, vol. 70, no. 3, pp. 267-275, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Da-Young Lee, Mi-Yeon Lee, and Ki-Chul Sung, “Prediction of Mortality with A Body Shape Index in Young Asians: Comparison with Body Mass Index and Waist Circumference,” Obesity, vol. 26, no. 6, pp. 1096-1103, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Yiyoung Lim, “A Development of Size System for the Abdomen-obese Adult Males According to the Lower-body Obesity-Type Analysis,” The Korean Fashion and Textile Research Journal, vol. 11, no. 6, pp. 904-910, 2009.
[Google Scholar] [Publisher Link]
[18] Kara L Crossley, Piers L Cornelissen, and Martin J Tovée, “What is an Attractive Body? Using an Interactive 3D Program to Create the Ideal Body for You and Your Partner,” Plos One, vol. 7, no. 11, pp. 1-11, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Anthony Wilson, “Body Shape Classifications of Males 26 to 35 Using Size USA Three-Dimensional Scan Data,” International Textile and Apparel Association Annual Conference Proceedings, vol. 76 no. 1, pp. 1-3, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Eonyou Shin, and Elahe Saeidi, “Whole Body Shapes and Fit Problems among Overweight and Obese Men in the United States,” Journal of Fashion Marketing and Management, vol. 27, no. 1, pp. 100-117, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Su-Jeong Hwang Shin, Cynthia L. Istook, and Jiinhee Lee, “Various Men's Body Shapes and Drops for Developing Menswear Sizing Systems in the United States,” Journal of the Korean Society of Clothing and Textiles, vol. 35, no. 12, pp. 1454-1465, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Keiko Watanabe, “Body Type Classification of the Three-dimensional Torso Shape of Japanese Men Aged 20 to 70 Years for Efficient Clothing Design,” Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Montreal QC, Canada, pp. 347-355, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Linghua Ran et al., “Classifications of Body Size for Chinese Females in Three Areas, Springer,” International Conference on Applied Human Factors and Ergonomics, Orlando, Florida, USA, pp. 323-331, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Pengpeng Cheng, Daoling Chen, and Jianping Wang, “Clustering of the Body Shape of the Adult Male by using Principal Component Analysis and Genetic Algorithm-BP Neural Network,” Soft Computing, vol. 24, no. 17, pp. 13219-13237, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[25] ISO 8559-1, “Size Designation of Clothes - Part 1: Anthropometric Definitions for Body Measurement, ISO, 2017.
[Publisher Link]
[26] Jongsuk Chun, “Men`s and Women`s Body Types in the Global Garment Sizing System,” The Research Journal of the Costume Culture, vol. 20, no. 6, pp. 923-936, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Vietnam Standard TCVN5782:2009, Standard Sizing Systems for Clothes, National Standards, 2009. [Online]. Available: https://vanbanphapluat.co/tcvn-5782-2009-he-thong-co-so-tieu-chuan-quan-ao#google_vignette [28] Stephen Pheasant, and Christine M. Haslegrave, Bodyspace: Anthropometry, Ergonomics and the Design of Work, 3rd ed., CRC Press, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Douglas Lind, William Marchal, and Samuel Wathen, Statistical Techniques in Business and Economics, 19th eds, McGraw-Hill, 2024.
[Google Scholar] [Publisher Link]
[30] Andy Field, Discovering Statistics Using IBM SPSS Statistics, 4th ed., SAGE Publisher, 2019.
[Google Scholar] [Publisher Link]
[31] The Global Health Observatory, Prevalence of overweight among adults, BMI >= 25 (age-standardized estimate) (%), World Health Organization, 2024. [Online]. Available: https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-overweight-among-adults-bmi--25-(age-standardized-estimate)-(-)
[32] Nurul Izzah Abd Rahman et al., “Anthropometric Measurements among Four Asian Countries in Designing Sitting and Standing Workstations,” Sādhanā, vol. 43, no. 1, pp. 1-9, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Meng-Jun Huang et al., “Comparison of the Predictive Value of Anthropometric Indicators for the Risk of Benign Prostatic Hyperplasia in Southern China,” Asian Journal of Andrology, vol. 25, no. 2, pp. 265-270, 2023.
[CrossRef] [Google Scholar] [Publisher Link]