Multiwindow Fusion for Wearable Activity Recognition

  • Oresti Banos
  • Juan-Manuel Galvez
  • Miguel Damas
  • Alberto Guillen
  • Luis-Javier Herrera
  • Hector Pomares
  • Ignacio Rojas
  • Claudia Villalonga
  • Choong Seon Hong
  • Sungyoung Lee
Conference paper

DOI: 10.1007/978-3-319-19222-2_24

Volume 9095 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Banos O. et al. (2015) Multiwindow Fusion for Wearable Activity Recognition. In: Rojas I., Joya G., Catala A. (eds) Advances in Computational Intelligence. IWANN 2015. Lecture Notes in Computer Science, vol 9095. Springer, Cham

Abstract

The recognition of human activity has been extensively investigated in the last decades. Typically, wearable sensors are used to register body motion signals that are analyzed by following a set of signal processing and machine learning steps to recognize the activity performed by the user. One of the most important steps refers to the signal segmentation, which is mainly performed through windowing approaches. In fact, it has been proved that the choice of window size directly conditions the performance of the recognition system. Thus, instead of limiting to a specific window configuration, this work proposes the use of multiple recognition systems operating on multiple window sizes. The suggested model employs a weighted decision fusion mechanism to fairly leverage the potential yielded by each recognition system based on the target activity set. This novel technique is benchmarked on a well-known activity recognition dataset. The obtained results show a significant improvement in terms of performance with respect to common systems operating on a single window size.

Keywords

Activity recognition Segmentation Windowing Wearable sensors Ensemble methods Data fusion 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Oresti Banos
    • 1
  • Juan-Manuel Galvez
    • 2
  • Miguel Damas
    • 2
  • Alberto Guillen
    • 2
  • Luis-Javier Herrera
    • 2
  • Hector Pomares
    • 2
  • Ignacio Rojas
    • 2
  • Claudia Villalonga
    • 2
  • Choong Seon Hong
    • 1
  • Sungyoung Lee
    • 1
  1. 1.Department of Computer EngineeringKyung Hee UniversityYongin-siKorea
  2. 2.Department of Computer Architecture and Computer TechnologyUniversity of GranadaGranadaSpain