Document Type
Conference Proceeding
Publication Date
7-2010
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.
Repository Citation
Banerjee, T.,
Keller, J. M.,
Skubic, M.,
& Abbott, C.
(2010). Sit-to-Stand Detection using Fuzzy Clustering Techniques. 2010 IEEE International Conference on Fuzzy Systems.
https://corescholar.libraries.wright.edu/knoesis/1114
DOI
10.1109/FUZZY.2010.5584843
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the IEEE International Conference on Fuzzy Systems, Barcelona, Spain, July 18-23, 2010.