Abstract
We are developing a personal activity recognition system that is practical, reliable, and can be incorporated into a variety of health-care related applications ranging from personal fitness to elder care. To make our system appealing and useful, we require it to have the following properties: (i) data only from a single body location needed, and it is not required to be from the same point for every user; (ii) should work out of the box across individuals, with personalization only enhancing its recognition abilities; and (iii) should be effective even with a cost-sensitive subset of the sensors and data features. In this paper, we present an approach to building a system that exhibits these properties and provide evidence based on data for 8 different activities collected from 12 different subjects. Our results indicate that the system has an accuracy rate of approximately 90% while meeting our requirements. We are now developing a fully embedded version of our system based on a cell-phone platform augmented with a Bluetooth-connected sensor board.
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Lester, J., Choudhury, T., Borriello, G. (2006). A Practical Approach to Recognizing Physical Activities. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds) Pervasive Computing. Pervasive 2006. Lecture Notes in Computer Science, vol 3968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11748625_1
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DOI: https://doi.org/10.1007/11748625_1
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