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Multisensor Fusion in Smartphones for Lifestyle Monitoring

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3 Author(s)
Ganti, R.K. ; Dept. of Comput. Sci., Univ. of Illinois, Urbana, IL, USA ; Srinivasan, S. ; Gacic, A.

Smartphones with diverse sensing capabilities are becoming widely available and pervasive in use. With the phone becoming a mobile personal computer, integrated applications can use multi-sensory data to derive information about the user's actions and the context in which these actions occur. This paper develops a novel method to assess daily living patterns using a smartphone equipped with microphones and inertial sensors. We develop a feature-space combination approach for fusion of information from sensors sampled at different rates and present a computationally light-weight algorithm to identify various high level activities. Preliminary results from an initial deployment among eight users indicate the potential for accurate, context-aware, and personalized sensing.

Published in:

Body Sensor Networks (BSN), 2010 International Conference on

Date of Conference:

7-9 June 2010