Sciweavers

Share
PERCOM
2010
ACM

Detecting activities from body-worn accelerometers via instance-based algorithms

8 years 5 months ago
Detecting activities from body-worn accelerometers via instance-based algorithms
The automatic and unobtrusive identification of user's activities is one of the challenging goals of context-aware computing. This paper discusses and experimentally evaluates instance-based algorithms to infer user's activities on the basis of data acquired from body-worn accelerometer sensors. We show that instance-based algorithms can classify simple and specific activities with high accuracy. In addition, due to their low requirements, we show how they can be implemented on severely resource-constrained devices. Finally, we propose mechanisms to take advantage of the temporal dimension of the signal, and to identify novel activities at run time. Key words: Context-aware Computing, Body-worn Sensors, Motion Classification.
Nicola Bicocchi, Marco Mamei, Franco Zambonelli
Added 20 May 2011
Updated 20 May 2011
Type Journal
Year 2010
Where PERCOM
Authors Nicola Bicocchi, Marco Mamei, Franco Zambonelli
Comments (0)
books