A Proposal to Classify Ways of Walking Patterns Using Spiking Neural Networks

  • Karen Fabiola MaresEmail author
  • Rosario Baltazar
  • Miguel Ángel Casillas
  • Víctor Zamudio
  • Lenin Lemus
Part of the Studies in Computational Intelligence book series (SCI, volume 749)


In this work the Spiking Neural Networks (SNNs) for the classification of ways of walking patterns is presented. The Differential Evolution (DE) Algorithm as an optimization technique was used for weights and delays settings. Two accelerometers, each one with three axes, were used to obtain simultaneous information on both legs. The information formed by nine features has been stored in a database: the first three correspond to the accelerations of x, y and z axis, next three correspond to the velocities which are obtained by doing an integration of the acceleration data for each axis and finally the positions x, y and z are calculated by the integration of velocities respectively.


Spiking neural networks Ambient assited living Walking patterns 



This work was partially supported by CONACYT and León Institute of Technology.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Karen Fabiola Mares
    • 1
    Email author
  • Rosario Baltazar
    • 1
  • Miguel Ángel Casillas
    • 1
  • Víctor Zamudio
    • 1
  • Lenin Lemus
    • 2
  1. 1.TecNM-Leon Institute of TechnologyLeonMexico
  2. 2.Polytechnic University of ValenciaValenciaSpain

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