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.
피인용 0
초록·키워드
This study systematically reviewed public datasets containing raw 3D motion analysis data related to gait, with the aim of selecting and presenting high-quality datasets suitable for research application. The criteria for dataset selection focused on research applicability, including detailed information such as participant demographics(e.g., gender and age), experimental equipment settings, and types of gait. Additionally, the structural integrity and completeness of the datasets were verified using open-source software and the R language based on the file formats (e.g., C3D, CSV, MAT). A total of 15 datasets were selected, most of which were accompanied by related studies aimed at providing public datasets. Analysis revealed that the datasets comprised data from 873 participants, including 457 males and 416 females, with ages ranging from 2 to 87 years, spanning children to older adults. The gait types included straight walking, stair climbing, and ramp walking. Data on both healthy participants and patients were also available. The public datasets selected and presented in this study offer detailed information on research methods, participant characteristics, and equipment settings, making them highly suitable for research application. Moreover, these datasets can support researchers facing data scarcity and contribute to the qualitative and quantitative advancement of gait research.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-092448693
