DocumentCode
2375453
Title
Unsupervised model generation for motion monitoring
Author
Weber, Markus ; Bleser, Gabriele ; Hendeby, Gustaf ; Reiss, Attila ; Stricker, Didier
Author_Institution
Augmented Vision, German Res. Center for Artificial Intell. (DFKI) GmbH, Kaiserslautern, Germany
fYear
2011
fDate
9-12 Oct. 2011
Firstpage
51
Lastpage
54
Abstract
This paper addresses two fundamental requirements of full body motion monitoring: (a) the ability to sense the input of the user and (b) the means to interpret the captured input. Appropriate technology in both areas is required for an interactive virtual reality system to provide feedback in a useful and natural way. This paper combines technologies for both areas: It develops a sensor fusion approach for capturing user input based on miniature on-body inertial and magnetic motion sensors. Furthermore, it presents work in progress to automatically generate models for motion patterns from the captured input. The technology is then used and evaluated in the context of a personalized virtual rehabilitation trainer application.
Keywords
medical computing; patient rehabilitation; sensor fusion; user interfaces; virtual reality; full body motion monitoring; magnetic motion sensor; on-body inertial sensor; personalized virtual rehabilitation trainer application; sensor fusion approach; unsupervised model generation; user input; virtual reality system; Biological system modeling; Hidden Markov models; Joints; Monitoring; Motion segmentation; Training; Viterbi algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location
Anchorage, AK
ISSN
1062-922X
Print_ISBN
978-1-4577-0652-3
Type
conf
DOI
10.1109/ICSMC.2011.6083641
Filename
6083641
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