Unsupervised model generation for motion monitoring
2011 (English)In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC): Workshop on Robust Machine Learning Techniques for Human Activity Recognition, IEEE , 2011Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
IEEE , 2011.
, IEEE International Conference on Systems, Man, and Cybernetics. Conference Proceedings, ISSN 1062-922X
Signal Processing Other Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:liu:diva-90522DOI: 10.1109/ICSMC.2011.6083641ISBN: 978-1-4577-0652-3OAI: oai:DiVA.org:liu-90522DiVA: diva2:613688
IEEE International Conference on Systems, Man, and Cybernetics (SMC 2011), 9-12 October 2011, Anchorage, AK, USA