Soft Computing

, Volume 17, Issue 2, pp 333–343 | Cite as

Human activity recognition based on a sensor weighting hierarchical classifier

  • Oresti Banos
  • Miguel Damas
  • Hector Pomares
  • Fernando Rojas
  • Blanca Delgado-Marquez
  • Olga Valenzuela


The analysis of daily living human behavior has proven to be of key importance to prevent unhealthy habits. The diversity of activities and the individuals’ particular execution style determine that several sources of information are normally required. One of the main issues is to optimally combine them to guarantee performance, scalability and robustness. In this paper we present a fusion classification methodology which takes into account the potential of the individual decisions yielded at both activity and sensor classification levels. Particularly tested on a wearable sensors based system, the method reinforces the idea that some parts of the body (i.e., sensors) may be specially informative for the recognition of each particular activity, thus supporting the ranking of the decisions provided by each associated sensor decision entity. Our method systematically outperforms the results obtained by traditional multiclass models which otherwise may require a high-dimensional feature space to acquire a similar performance. The comparison with other activity-recognition fusion approaches also demonstrates our model scales significantly better for small sensor networks.


Multisource fusion Hierarchical classification Weighted decision Binary classifiers Activity recognition Wearable sensors 



We want to express our gratitude to Prof. Stephen S. Intille, Technology Director of the HouseN Consortium in the MIT Department of Architecture for the experimental data provided. This work was supported in part by the Spanish CICYT Project TIN2007-60587, Junta de Andalucia Projects P07-TIC-02768 and P07-TIC-02906, the CENIT project AmIVital, of the “Centro para el Desarrollo Tecnolgico Industrial” (CDTI-Spain), the FPU Spanish Grant AP2009-2244 and the UGR Spanish Grant “Iniciación a la Investigación 2010/2011”.


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Oresti Banos
    • 1
  • Miguel Damas
    • 1
  • Hector Pomares
    • 1
  • Fernando Rojas
    • 1
  • Blanca Delgado-Marquez
    • 2
  • Olga Valenzuela
    • 3
  1. 1.Department of Computer Architecture and Computer TechnologyCITIC-UGR, University of GranadaGranadaSpain
  2. 2.Department of International EconomicsUniversity of GranadaGranadaSpain
  3. 3.Department of Applied MathematicsUniversity of GranadaGranadaSpain

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