Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker

Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Tung, Allan Caine
Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, PMLR R8:391-399, 2010.

Abstract

Rollating walkers are popular mobility aids used by older adults to improve balance con- trol. There is a need to automatically recog- nize the activities performed by walker users to better understand activity patterns, mo- bility issues and the context in which falls are more likely to happen. We design and com- pare several techniques to recognize walker related activities. A comprehensive evalua- tion with control subjects and walker users from a retirement community is presented.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR8-omar10a, title = {Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker}, author = {Omar, Farheen and Sinn, Mathieu and Truszkowski, Jakub and Poupart, Pascal and Tung, James and Caine, Allan}, booktitle = {Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence}, pages = {391--399}, year = {2010}, editor = {Grünwald, Peter and Spirtes, Peter}, volume = {R8}, series = {Proceedings of Machine Learning Research}, month = {08--11 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r8/main/assets/omar10a/omar10a.pdf}, url = {https://proceedings.mlr.press/r8/omar10a.html}, abstract = {Rollating walkers are popular mobility aids used by older adults to improve balance con- trol. There is a need to automatically recog- nize the activities performed by walker users to better understand activity patterns, mo- bility issues and the context in which falls are more likely to happen. We design and com- pare several techniques to recognize walker related activities. A comprehensive evalua- tion with control subjects and walker users from a retirement community is presented.}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker %A Farheen Omar %A Mathieu Sinn %A Jakub Truszkowski %A Pascal Poupart %A James Tung %A Allan Caine %B Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2010 %E Peter Grünwald %E Peter Spirtes %F pmlr-vR8-omar10a %I PMLR %P 391--399 %U https://proceedings.mlr.press/r8/omar10a.html %V R8 %X Rollating walkers are popular mobility aids used by older adults to improve balance con- trol. There is a need to automatically recog- nize the activities performed by walker users to better understand activity patterns, mo- bility issues and the context in which falls are more likely to happen. We design and com- pare several techniques to recognize walker related activities. A comprehensive evalua- tion with control subjects and walker users from a retirement community is presented. %Z Reissued by PMLR on 04 October 2026.
APA
Omar, F., Sinn, M., Truszkowski, J., Poupart, P., Tung, J. & Caine, A.. (2010). Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker. Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R8:391-399 Available from https://proceedings.mlr.press/r8/omar10a.html. Reissued by PMLR on 04 October 2026.

Related Material