Simple classification of walking activities using commodity smart phones


Autoria(s): Fitz-Walter, Zachary; Tjondronegoro, Dian W.
Data(s)

2010

Resumo

People interact with mobile computing devices everywhere, while sitting, walking, running or even driving. Adapting the interface to suit these contexts is important, thus this paper proposes a simple human activity classification system. Our approach uses a vector magnitude recognition technique to detect and classify when a person is stationary (or not walking), casually walking, or jogging, without any prior training. The user study has confirmed the accuracy.

Identificador

http://eprints.qut.edu.au/46737/

Publicador

ACM

Relação

DOI:10.1145/1738826.1738911

Fitz-Walter, Zachary & Tjondronegoro, Dian W. (2010) Simple classification of walking activities using commodity smart phones. In OZCHI '09 Proceedings of the 21st Annual Conference of the Australian Computer-Human Interaction Special Interest Group: Design: Open 24/7, ACM, The University of Melbourne, Melbourne, pp. 409-412.

Direitos

Copyright ACM 2010

Fonte

Faculty of Science and Technology; Information Systems

Palavras-Chave #080600 INFORMATION SYSTEMS #080602 Computer-Human Interaction #activity classification #accelerometer #mobile computing #ubiquitous computing #context aware
Tipo

Conference Paper