Fall among the elderly is an important health issue. Fall detection and movement tracking techniques are therefore instrumental in dealing with this issue. This thesis responds to the
challenge of classifying different movement types as a part of a system designed to fulfill the need for a wearable device to collect data for fall and near-fall analysis. Four different fall activities (forward, backward, left and right),
three normal activities (standing, walking and lying down) and near-fall situations are identified and detected. Different machine
learning algorithms are compared and the best one is used for the real time classification. The comparison is made using Waikato Environment for Knowledge Analysis or in short WEKA. The system also has the ability to adapt to different gaits of different people. A feature selection algorithm is also introduced to reduce the number
of features required for the classification problem.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:SSU.etd-12222009-144628 |
| Date | 04 January 2010 |
| Creators | Ralhan, Amitoz Singh |
| Contributors | Ko, Seok-Bum, Teng, Daniel, Ludwig, Simone, Dinh, Anh |
| Publisher | University of Saskatchewan |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://library.usask.ca/theses/available/etd-12222009-144628/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Saskatchewan or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 0.0022 seconds