Using Echo State Networks to Classify Unscripted, Real-World Punctual Activity

  • Doug P. HuntEmail author
  • Dave Parry
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 517)


This paper employs an Echo State Network (ESN) to classify unscripted, real-world, punctual activity using inertial sensor data collected from horse riders. ESN has been shown to be an effective black-box classifier for spatio-temporal data and so we suggest that ESN could be useful as a classifier for punctual human activities and as a result a potential tool for wearable technologies. The aim of this study is to provide an example classifier, illustrating the applicability of ESN as a punctual activity classifier for the chosen problem domain. This is part of a wider set of work to build a wearable coach for equestrian sport.


Echo State Network Punctual activity classification Spatio-temporal Equestrian sport Wearable technology Wearable coach 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Auckland University of TechnologyAucklandNew Zealand

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