Name
Abstract | ||
|---|---|---|
An investigation of a new, inexpensive depth camera device, the Microsoft Kinect, for passive gait assessment in home environments is presented. In order to allow older adults to safely continue living in independent settings as they age, the ability to assess their risk of falling, along with detecting the early onset of illness and functional decline, is essential. Daily measurements of temporal and spatial gait parameters would greatly facilitate such an assessment. Ideally, these measurements would be obtained passively, in normal daily activity, without the need for wearable devices or expensive equipment. In this work, the use of the inexpensive Microsoft Kinect for obtaining measurements of temporal and spatial gait parameters is evaluated against an existing web-camera based system, along with a Vicon marker-based motion capture system for ground truth. Techniques for extracting gait parameters from the Kinect data are described, as well as the potential advantages of the Kinect over the web-camera system for passive, in-home gait assessment. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.3233/AIS-2011-0124 | JAISE |
Keywords | Field | DocType |
gait,kinect,smart environments | Motion capture,Computer vision,Smart environment,Gait,Simulation,Computer science,Fall risk,Gait analysis,Human–computer interaction,Ground truth,Artificial intelligence,Wearable technology | Journal |
Volume | Issue | ISSN |
3 | 4 | 1876-1364 |
Citations | PageRank | References |
52 | 4.66 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erik E. Stone | 1 | 381 | 31.42 |
| Marjorie Skubic | 2 | 1045 | 105.36 |