This study aimed to identify changes in upper body measurements and body shape types among women over a 10-year period based on data from the 6th and 8th Size Korea Anthropometric Surveys. The study used regression analysis to explore the relationship between various dimensions, enabling the prediction of different upper body dimensions based on height and waist circumference. The sample consisted of 1,179 women in their 20s who participated in the 6th (2010) and 8th (2020) Size Korea Anthropometric Surveys, with 33 items analyzed. Initially, most items, except those related to height, exhibited larger values in the 8th Survey than in the 6th, suggesting a general increase in the upper body dimensions of females in their 20s over the 10-year period. Subsequent factor analysis revealed three factors crucial for determining the upper body shape of women in this age group. The body shapes were then categorized into four distinct clusters. Regression analysis indicated that both waist circumference and height significantly influence most of the measured items, with waist circumference having a more substantial impact in most models. Through this research, we aim to provide foundational data that reflects the evolving upper body shapes of women in their 20s to enhance clothing production and improve the sizing system.

This study aimed to analyze adult men’s body sizes and shapes and suggest size specifications to provide preliminary data to academia and industries. A total of 814 adult men aged 30-44 were selected from the 7th Size Korea data, and 55 direct upper body measurement and calculation items were analyzed using SPSS 25.0. In individual Individual differences, thickness, circumference, and width were high, and height and length were low. Height above the waist base line and shoulder dimension decreased in early 40s age group, while height below the waist base line declined as age increased. In addition, buttocks shape changes were found in early 40s age group. According to factor analysis, ‘upper body and upper-extremity horizontal size’, ‘torso height and upper extremity length’, ‘shoulder dimension’, ‘upper body length’ and ‘shoulder angle’ were derived. Using clustering analysis, four different body types were classified: i) big abdomen with flat chest, ii) slender with big, raised shoulders, iii) dwarfish with small, droopy shoulders, and iv) obese with large shoulders. ‘Slender with big, raised shoulders’ was a typical body shape among men aged 30-44. In older participants, the ‘big abdomen with flat chest’ ratio was low, while ‘obese with large shoulders’ was more common. This study proposed size specifications by body type considering the above characteristics.

The aim of this study was to investigate the change in women’s somatotype with aging. The subjects were 1,123 women aged 40~69. Their anthropometric data were from the 6th Size Korea. The data were analyzed by factor analysis and cluster analysis. Seven factors were extracted: body mass, body length, back shoulder, arm length factor, front interscye factor, body rise factor, and shoulder angle. The upper body types of middle-aged and elderly women were classified into five types: skinny, short stout body type with forward posture, composite, tall & full body type, and short & skinny. The skinny and composite body type appeared more often than the short stout body type in the early 40s of Korean women. Starting in the mid-50s, composite body type was less often found. However, the number of women with short stout body type increased. In the 60s, the number of women with short stout and tall & full body types decreased. These results reveal that the body types of middle-aged and elderly women changed with some pattern with aging. And women in their early 40s, mid-50s, and 60s women had different body shapes and postures.

유아용 체감형 게임은 유아 놀이 공간 축소로 인한 안전한 유아 놀이 공간 부족에 대한 해결책 중 하나로 대두되고 있다. 이에 따라 본 연구에서는 유아용 체감형 게임 인터페이스에 활용 가능하고 유아의 동작 특성이 고려된 유아 교육적으로 적합하고 체계적으로 정리된 유아 동작 데이터베이스가 필요성을 제기하고 유아의 상체 동작을 선정하여 데이터베이스를 구축했다. 동작 데이터베이스는 센서와 카메라의 두 디바이스를 모두 사용한 7개의 한 손 동작과 카메라만을 사용한 7개의 두 손 동작 데이터로 구성되었다. 유아 동작 데이터베이스는 각 연령별로 남자 유아 5명, 여자 유아 5명으로 만3세에서 만 5세의 유아 30명을 대상으로 동작이 수집되었다. 데이터베이스는 총 14개 동작을 한 동작마다 3번씩 반복하여 수집하였다. 수집된 데이터베이스는 유아용 체감형 게임에 적용 가능하고 유아가 쉽게 따라하는 것이 가능한 동작들로써 연구용으로 외부에 공개 및 배포되어 유아 대상의 체감형 게임 개발에 도움이 될 것이다.