A public dataset for 3D motion analysis in gait research: Systematic review

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.