Accelerometer Signal Features and Classification Algorithms for Positioning Applications

M. Susi, D. Borio, G. Lachapelle

Abstract:	The continuous development of Micro Electro-Mechanical Sensors (MEMSs) and their integration into cell-phones and other mobile devices is pushing the design of new algorithms capable of determining the user activity. Determining what the user is doing allows one to bound his displacement and provide information about his location. The design of such algorithms is a classification problem where the different classes are specified by the MEMS location and user activity. In this paper, MEMS accelerometer signals are analyzed in different domains and several features are selected for the design of classification algorithms. Frequency domain analysis is performed as a function of the user velocity and sensor location, showing the potential of the selected features even when the MEMS is not placed on the user foot. The selected features are finally integrated into three different classification algorithms whose characteristics are analyzed and compared under several operating conditions.
Published in:	Proceedings of the 2011 International Technical Meeting of The Institute of Navigation January 24 - 26, 2011 Catamaran Resort Hotel San Diego, CA
Pages:	158 - 169
Cite this article:	Susi, M., Borio, D., Lachapelle, G., "Accelerometer Signal Features and Classification Algorithms for Positioning Applications," Proceedings of the 2011 International Technical Meeting of The Institute of Navigation, San Diego, CA, January 2011, pp. 158-169.
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