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Towards Human Energy Expenditure Estimation Using Smart Phone Inertial Sensors

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Ambient Intelligence (AmI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8309))

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Abstract

This paper is focused on a machine-learning approach for estimating human energy expenditure during sport and normal daily activities. The paper presents technical feasibility assessment that analyses requirements and applicability of smart phone sensors to human energy expenditure. The paper compares and evaluates three different sensor configuration sets: (i) a heart rate monitor and two standard inertial sensors attached to the users thigh and chest; (ii) a heart rate monitor with an embedded inertial sensor and a smart phone carried in the pocket; and (iii) only a smart phone carried in the pocket. The accuracy of the models is validated against indirect calorimetry using the Cosmed system and compared to a commercial device for energy expenditure SenseWear armband. The results show that models trained using relevant features can perform comparable or even better than available commercial device.

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Author information

Authors and Affiliations

  1. Department of Intelligent Systems, Jožef Stefan Institute, Jamova ceta 39, 1000, Ljubljana, Slovenia

    Božidara Cvetković, Boštjan Kaluža & Mitja Luštrek

  2. Faculty of Sports, University of Ljubljana, Gortanova 22, Ljubljana, Slovenia

    Radoje Milić

  3. Jožef Stefan International Postgradute School, Jamova ceta 39, 1000, Ljubljana, Slovenia

    Božidara Cvetković, Boštjan Kaluža & Mitja Luštrek

Authors
  1. Božidara Cvetković
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  2. Boštjan Kaluža
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  3. Radoje Milić
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  4. Mitja Luštrek
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Middlesex University, London, UK

    Juan Carlos Augusto

  2. Fraunhofer IGD, Fraunhoferstrasse 5, 64283, Darmstadt, Germany

    Reiner Wichert

  3. School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    Rem Collier

  4. Delft University of Technology, 2628 CE, Delft, The Netherlands

    David Keyson

  5. Department of Computer Engineering, Boğaziçi University, Bebek, 34342, Istanbul, Turkey

    Albert Ali Salah

  6. School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore

    Ah-Hwee Tan

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© 2013 Springer International Publishing Switzerland

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Cvetković, B., Kaluža, B., Milić, R., Luštrek, M. (2013). Towards Human Energy Expenditure Estimation Using Smart Phone Inertial Sensors. In: Augusto, J.C., Wichert, R., Collier, R., Keyson, D., Salah, A.A., Tan, AH. (eds) Ambient Intelligence. AmI 2013. Lecture Notes in Computer Science, vol 8309. Springer, Cham. https://doi.org/10.1007/978-3-319-03647-2_7

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  • DOI: https://doi.org/10.1007/978-3-319-03647-2_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03646-5

  • Online ISBN: 978-3-319-03647-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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