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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Banerjee, T. Keller, J.M. Skubic, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: Electr. & Comput. Eng. Dept., Univ. of Missouri, Columbia, MO, USA (Banerjee, T.; Keller, J.M.; Skubic, M.) |
| Abstract | As a part of our passive fall risk assessment research in home environments, we present a method to identify older residents using features extracted from their gait information from a single depth camera. Depth images have been collected continuously for about eight months from several apartments at a senior housing facility. Shape descriptors such as bounding box information and image moments were extracted from silhouettes of the depth images. The features were then clustered using Possibilistic C Means for resident identification. This technology will allow researchers and health professionals to gather more information on the individual residents by filtering out data belonging to non-residents. Gait related information belonging exclusively to the older residents can then be gathered. The data can potentially help detect changes in gait patterns which can be used to analyze fall risk for elderly residents by passively observing them in their home environments. |
| Sponsorship | IEEE Eng. Medicine Biol. Soc. |
| Starting Page | 5102 |
| Ending Page | 5105 |
| File Size | 828934 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441198 |
| ISSN | 1557170X |
| e-ISBN | 9781457717871 |
| DOI | 10.1109/EMBC.2012.6347141 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-08-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Monitoring Green products Phase change materials Clustering algorithms |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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