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Step Count and Classification Using Sensor Information Fusion

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Ambient Intelligence - Software and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 376))

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Abstract

In order to suppress the GNSS (Global Navigation Satellite System) limitation to track persons in indoor or in dense environments, a pedestrian inertial navigation system can be used. However, this type of systems have huge location estimation errors due to the Pedestrian Dead Reckoning (PDR) characteristics and the use of low-cost inertial sensors. To suppress some of these errors we propose a system that uses several sensors spread in person’s body combined with information fusion techniques. Information fusion techniques provide lighter algorithms implementations, to count and classify the type of step, to run in mobile devices. Thus, improving pedestrian inertial navigation systems accuracy.

This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). Ricardo also acknowledge FCT for the support of his work through the PhD grant SFRH/DB/70248/2010.

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Author information

Authors and Affiliations

  1. GECAD—Knowledge Engineering and Decision Support Research Center, School of Engineering—Polytechnic of Porto, Porto, Portugal

    Ricardo Anacleto, Lino Figueiredo, Ana Almeida & António Meireles

  2. CCTC—Computer Science and Technology Center, University of Minho, Braga, Portugal

    Paulo Novais

Authors
  1. Ricardo Anacleto
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  2. Lino Figueiredo
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  3. Ana Almeida
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  4. Paulo Novais
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  5. António Meireles
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Corresponding author

Correspondence to Ricardo Anacleto .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering Department, Qatar University, College of Engineering, Doha, Qatar

    Amr Mohamed

  2. Departamento de Informatica, ALGORITMI Centre, University of Minho, Braga, Portugal

    Paulo Novais

  3. Escola Superior de Tecnologia e Gestäo de Leiria, Instituto Politécnico de Leiria, Leiria, Portugal

    António Pereira

  4. Departamento de Informática y Automática, University of Salamanca, Salamanca, Spain

    Gabriel Villarrubia González

  5. Departamento de Sistemas Informáticos, University of Castilla-La Mancha, Albacete, Spain

    Antonio Fernández-Caballero

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Anacleto, R., Figueiredo, L., Almeida, A., Novais, P., Meireles, A. (2015). Step Count and Classification Using Sensor Information Fusion. In: Mohamed, A., Novais, P., Pereira, A., Villarrubia González, G., Fernández-Caballero, A. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent Systems and Computing, vol 376. Springer, Cham. https://doi.org/10.1007/978-3-319-19695-4_9

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  • DOI: https://doi.org/10.1007/978-3-319-19695-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19694-7

  • Online ISBN: 978-3-319-19695-4

  • eBook Packages: EngineeringEngineering (R0)

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