International virtual human body (VHB) standards from the International Organization for Standardization (ISO) specifically used in virtual garment systems in the apparel field, as suggested in ISO/TC 133/WG 2 (Working group 2), contain fundamental content regarding definitions of terms, attributes of composition, and the expression and alteration of VHBs. As the first attempt in the series of international standards dealing with VHBs, this study has dealt with fundamental content related to VHB size. Additional standardization is required to allow the size and shape of VHB to be reproducible. Therefore, this study suggests academic and industrial requirements from the perspective of standardization to identify and solve issues regarding the reproduction of human bodies in terms of VHB size and shape. This study is meaningful in that it provides an overview of current VHB standardization efforts, related proceedings, and additionally required assignments. The suggested industrial and academic requirements are anticipated to be helpful in the systematic development and utilization of VHB and general standardization work.

Based on 3D body scanning, this study developed the corresponding measurement-based patternmaking (CMP) method for leggings that could systematically provide an excellent fit and control tightness for different body parts. The CMP method for leggings was qualitatively validated by comparing the fit suitability of the produced leggings prototypes through a wear test. The results suggest that the CMP method is an option to design leggings with outstanding suitability in terms of appearance satisfaction, size satisfaction, compression satisfaction, usefulness in movement, ease of movement, ease in donning and doffing for different body parts. In particular, the graduated application percentage (GAP) provided an advantage in usefulness in movement, while the fixed application percentage (FAP) showed an advantage in ease in donning and doffing. As such, this study suggests selecting the CMP method of the application percentage (AP) depending on the purpose of use. This study demonstrated that the proposed method ensured validity in directly implementing a leggings pattern with 3D body scanning and body measurement alone.

This study aims to improve soldiers' mission performance and protect them from safety accidents by establishing an optimal sizing system that considers the fit of the tactical gloves and the efficiency of production and supply. First, the wearing condition of tactical gloves was investigated through in-depth interviews and surveys. The optimal glove fit and loss coefficient ratio was then analyzed through a glove size selection experiment. Finally, the sizing system was optimized and verified by comparing the coverage rate to the current sizing system. Results indicated that the empirically derived loss coefficient ratio was 0.075 and the optimal sizing system for tactical gloves was S-hand length: 168, hand width: 81, M-hand length: 177, hand width: 83, L-hand length: 184, hand width: 86, XL-hand length: 191, hand width: 89, respectively. The coverage rate of the optimal sizing system proposed in this study was 86.4%, showing an improvement of approximately 21.1% compared to the current sizing system (65.3%). In conclusion, the optimal sizing system for tactical gloves proposed in this study can be a realistic solution, as it improved the coverage rate by 21.1% without incurring additional costs for production or hindering the efficiency of supply.

Research purpose: This study aimed to lay a research foundation for smart hand wearable design by classifying the right-hand data of 4545 adults aged 20 to 69. Further, to increase the practical applicability of the hand classification system, a hand type discrimination method and regression equations for the hand dimensions of each type were presented. Methods: This study statistically analyzed eighth Size Korea data with IBM SPSS Ver.26.0. Cluster analysis was performed to classify both finger length and circumference type. Discriminant analysis was conducted, yielding discriminant functions to aid potential smart hand wearable wearers in self-diagnosing their hand types. Linear regression analysis yielded regression equations for the detailed finger dimensions for the pattern-making of smart hand wearables. Results: The finger length type was categorized into four types: the Uphill type, Downhill type, Mountain type, and Horizon type for both men’s and women’s hands. The finger circumference type was categorized into two types, the Cone and Cylinder types, for both men’s and women’s hands. The discriminant function showed a mean accuracy rate of 89.9% and the regression equations a mean explanatory power of 72.9%. Conclusion: The hand classification system proposed in this study aimed to improve the fingertip fit of smart hand wearable products by analyzing the configuration of motion tracking gloves or haptic gloves. In addition, considering the practical applicability for both wearers and designers of smart hand wearables, a discrimination method of finger types for wearers’ self-diagnosis and regression functions of finger dimensions for designers’ pattern making were provided.