A Practical Approach to Recognizing Physical Activities

  • Jonathan Lester
  • Tanzeem Choudhury
  • Gaetano Borriello
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3968)


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.


Wireless Sensor Network Cell Phone Recognition Accuracy Activity Recognition Spectral Entropy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jonathan Lester
    • 1
  • Tanzeem Choudhury
    • 2
  • Gaetano Borriello
    • 2
    • 3
  1. 1.Department of Electrical EngineeringUniversity of WashingtonSeattleUSA
  2. 2.Intel Research SeattleSeattleUSA
  3. 3.Department of Computer ScienceUniversity of WashingtonSeattleUSA

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