Title
Unsupervised model generation for motion monitoring.
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.
Year
DOI
Venue
2011
10.1109/ICSMC.2011.6083641
SMC
Keywords
Field
DocType
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
Inertial frame of reference,Signal processing,Computer vision,Virtual reality,Work in process,Computer science,Sensor fusion,Artificial intelligence,Hidden Markov model,User interface,Machine learning,Virtual rehabilitation
Conference
ISSN
Citations 
PageRank 
1062-922X
0
0.34
References 
Authors
4
5
Name
Order
Citations
PageRank
Markus Weber116620.97
Gabriele Bleser224127.76
Gustaf Hendeby321621.37
Attila Reiss441024.01
Didier Stricker51266138.03