인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The purpose of this study is to comprehend patterns in order to make functional yoga slacks. Yoga slacks are significant to have functional aspect and acceptability of body motion because of its tightness. The study needs to recognize the change of human body surface on movement. 3D body scan system used to collect a data of body shape and figure out the areas of body surface which are divided by standard points. Due to this research, mid-aged women are selected between 45 and 54 years old having done yoga and the body size of the women is based on the 6th korean standard body size. Selected women perform a standing poses and four fundamental yoga poses while scanning the whole body by 3D body scanner. The areas of 3D scanned body surface are calculated to analyze the change of increase and decrease according to yoga poses. The change of areas is shown by visible graph to find the parts of protocol parts by 3D data. Each data overlaps on the standing poses pattern. The protocol of patterns means that the area is not concerned by the body movement and it suggests to make lines of pattern of the unconstrained way. The result of the study is that pattern protocol areas are mid pelvic, inside below calf, outside pelvic, outside thigh areas in the front body and outside crotch, outside thigh, outside calf areas in the back part. The selected protocol areas means that the zone would be able to change the lines of pattern depending on pattern makers or designers in their work process. The study suggests a concrete data to make the functional development yoga slacks and investigate pattern protocol areas thorough movement assessment. This can help mid-aged women to recognize the change of the body surface area by 3D body scanning method and the market of yoga sportswear at fashion industry can be expanded through active studies.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2016-300-001971328
