Abstract
The ability to rise from a chair is an important parameter to assess the balance deficits of a person. In particular, this can be an indication of risk for falling in elderly persons. Our goal is automated assessment of fall risk using video data. Towards this goal, we present a simple yet effective method of detecting transition, i.e. sit-to-stand and stand-to-sit, from image frames using fuzzy clustering methods on image moments. The technique described in this paper is shown to be robust even in the presence of noise and has been tested on several data sequences using different subjects yielding promising results.
Original language | American English |
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Title of host publication | 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 |
Publisher | IEEE |
ISBN (Electronic) | 978-1-4244-6921-5, 978-1-4244-6920-8 |
ISBN (Print) | 978-1-4244-6919-2 |
DOIs | |
State | Published - Sep 23 2010 |
Event | 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - Barcelona, Spain Duration: Jul 18 2010 → Jul 23 2010 |
Conference
Conference | 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 |
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Country/Territory | Spain |
City | Barcelona |
Period | 7/18/10 → 7/23/10 |
ASJC Scopus Subject Areas
- Artificial Intelligence
- Computational Theory and Mathematics
Keywords
- Government
- Fuzzy Rough Set
Disciplines
- Bioinformatics
- Communication Technology and New Media
- Databases and Information Systems
- OS and Networks
- Science and Technology Studies