DRAG: A Database for Recognition and Analysis of Gait

A novel approach is proposed for creating a standardized and comprehensive database for gait analysis. The field of gait analysis is gaining increasing attention for applications such as visual surveillance, human-computer interfaces, and gait recognition and rehabilitation. Numerous algorithms have been developed for analyzing and processing gait data; however, a standard database for their systematic evaluation does not exist. Instead, existing gait databases consist of subsets of kinematic, kinetic, and electromyographic activity recordings by different investigators, at separate laboratories, and under varying conditions. Thus, the existing databases are neither homogenous nor sufficiently populated to statistically validate the algorithms. In this paper, a methodology for creating a database is presented, which can be used as a common ground to test the performance of algorithms that rely upon external marker data, ground reaction loading data, and/or video images. The database consists of: (i) synchronized motion-capture data (3D marker data) obtained using external markers, (ii) computed joint angles, and (iii) ground reaction loading acquired with plantar pressure insoles. This database could be easily expanded to include synchronized video, which will facilitate further development of video-based algorithms for motion tracking. This eventually could lead to the realization of markerless gait tracking. Such a system would have extensive applications in gait recognition, as well as gait rehabilitation. The entire database (marker, angle, and force data) will be placed in the public domain, and made available for downloads over the World Wide Web.