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K-Sense: Towards a Kinematic Approach for Measuring Human Energy Expenditure

  • Conference paper
Wireless Sensor Networks (EWSN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8354))

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Abstract

Accurate energy expenditure monitoring will be an essential part of medical diagnosis in the future, enabling individually-tailored just-in-time interventions. However, there are currently no real-time monitors that are practical for continuous daily use. In this paper, we introduce the K-Sense energy expenditure monitor that uses inertial measurement units (IMUs) mounted to an individual’s wrist and ankle with elastic bands to determine angular velocity and position. The system utilizes kinematics to determine the amount of energy required for each limb to achieve its current movement. Our empirical evaluation includes over 3,000,000 individual data samples across 12 individuals and the results indicate that the system can estimate total energy expenditure with a 92 percent accuracy on average.

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Author information

Authors and Affiliations

  1. University of Memphis, Memphis, TN, USA

    Kazi I. Zaman, Anthony White, Sami R. Yli-Piipari & Timothy W. Hnat

Authors
  1. Kazi I. Zaman
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  2. Anthony White
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  3. Sami R. Yli-Piipari
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  4. Timothy W. Hnat
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Editor information

Editors and Affiliations

  1. Ming Hsieh Faculty, Department of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, 90089, Los Angeles, CA, USA

    Bhaskar Krishnamachari

  2. Center for Scientific and Technological Research (IRST), Fondazione Bruno Kessler (FBK), Via Sommarive 18, 38123, Povo, Italy

    Amy L. Murphy

  3. Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, OX1 3QD, Oxford, UK

    Niki Trigoni

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© 2014 Springer International Publishing Switzerland

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Zaman, K.I., White, A., Yli-Piipari, S.R., Hnat, T.W. (2014). K-Sense: Towards a Kinematic Approach for Measuring Human Energy Expenditure. In: Krishnamachari, B., Murphy, A.L., Trigoni, N. (eds) Wireless Sensor Networks. EWSN 2014. Lecture Notes in Computer Science, vol 8354. Springer, Cham. https://doi.org/10.1007/978-3-319-04651-8_11

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  • DOI: https://doi.org/10.1007/978-3-319-04651-8_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04650-1

  • Online ISBN: 978-3-319-04651-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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