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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)

Abstract

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.

Keywords

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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