Abstract
Human mobility is an important health indicator, especially for older adults potentially transitioning to frailty. Currently, the analysis of human mobility is based on expensive or intrusive technologies. Depth camera devices, such as the Microsoft Kinect, have been demonstrated to be a valid low-cost alternative for assessing a persons mobility. In this work, mobility assessment is approached based on the automated analysis of the Timed Up & Go (TUG) test. Two methods based on depth and on skeleton data are proposed. In order to evaluate the proposed mobility analysis approaches, human mobility datasets have been acquired and manually labeled. It is shown that human mobility analysis based on off the shelf 3d sensors have the potential to assess functional decline of older adults.
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