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A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living

  • Giuseppe Amato
  • Davide Bacciu
  • Stefano Chessa
  • Mauro Dragone
  • Claudio Gallicchio
  • Claudio Gennaro
  • Hector Lozano
  • Alessio Micheli
  • Gregory M. P. O’Hare
  • Arantxa Renteria
  • Claudio Vairo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 476)

Abstract

We present a data benchmark for the assessment of human activity recognition solutions, collected as part of the EU FP7 RUBICON project, and available to the scientific community. The dataset provides fully annotated data pertaining to numerous user activities and comprises synchronized data streams collected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.

Keywords

Ambient assisted living Human Activity Recognition Datasets 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Giuseppe Amato
    • 1
  • Davide Bacciu
    • 2
  • Stefano Chessa
    • 1
    • 2
  • Mauro Dragone
    • 3
  • Claudio Gallicchio
    • 2
  • Claudio Gennaro
    • 1
  • Hector Lozano
    • 4
  • Alessio Micheli
    • 2
  • Gregory M. P. O’Hare
    • 5
  • Arantxa Renteria
    • 4
  • Claudio Vairo
    • 1
  1. 1.CNR-ISTIPisaItaly
  2. 2.Department of Computer ScienceUniversity of PisaPisaItaly
  3. 3.Sensors, Signals and SystemsHeriot-Watt UniversityEdinburghUK
  4. 4.TecnaliaBilbaoSpain
  5. 5.University College DublinDublinIreland

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