Novel Method for Feature-Set Ranking Applied to Physical Activity Recognition

  • Oresti Baños
  • Héctor Pomares
  • Ignacio Rojas
Conference paper

DOI: 10.1007/978-3-642-13025-0_65

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6097)
Cite this paper as:
Baños O., Pomares H., Rojas I. (2010) Novel Method for Feature-Set Ranking Applied to Physical Activity Recognition. In: García-Pedrajas N., Herrera F., Fyfe C., Benítez J.M., Ali M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science, vol 6097. Springer, Berlin, Heidelberg

Abstract

Considerable attention is recently being paid in e-health and e-monitoring to the recognition of motion, postures and physical exercises from signal activity analysis. Most works are based on knowledge extraction using features which permit to make decisions about the activity realized, being feature selection the most critical stage. Feature selection procedures based on wrapper methods or ‘branch and bound’ are highly computationally expensive. In this paper, we propose an alternative filter method using a feature-set ranking via a couple of two statistical criteria, which achieves remarkable accuracy rates in the classification process.

Keywords

Activity Recognition Feature Selection Ranking 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Oresti Baños
    • 1
  • Héctor Pomares
    • 1
  • Ignacio Rojas
    • 1
  1. 1.Department of Computer Architecture and Computer TechnologyUniversity of GranadaGranadaSpain

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