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Validity of Consumer Activity Monitors and an Algorithm Using Smartphone Data for Measuring Steps during Different Activity Types

Author

Listed:
  • Verena Hartung

    (Department of Sport Science and Sport, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, Germany)

  • Mustafa Sarshar

    (Department of Sport Science, Division of Health and Physical Activity, Otto-von-Guericke University, 39104 Magdeburg, Germany)

  • Viktoria Karle

    (Department of Education, University of Regensburg, 93040 Regensburg, Germany)

  • Layal Shammas

    (Zentrum für Telemedizin Bad Kissingen, 97688 Bad Kissingen, Germany)

  • Asarnusch Rashid

    (Zentrum für Telemedizin Bad Kissingen, 97688 Bad Kissingen, Germany)

  • Paul Roullier

    (Zentrum für Telemedizin Bad Kissingen, 97688 Bad Kissingen, Germany)

  • Caroline Eilers

    (Department of Neurology, Klinikum Würzburg Mitte gGmbH, 97070 Würzburg, Germany)

  • Mathias Mäurer

    (Department of Neurology, Klinikum Würzburg Mitte gGmbH, 97070 Würzburg, Germany)

  • Peter Flachenecker

    (Neurological Rehabilitation Center Quellenhof, 75323 Bad Wildbad, Germany)

  • Klaus Pfeifer

    (Department of Sport Science and Sport, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, Germany)

  • Alexander Tallner

    (Department of Sport Science and Sport, Friedrich-Alexander University Erlangen-Nürnberg, 91058 Erlangen, Germany)

Abstract

Background : Consumer activity monitors and smartphones have gained relevance for the assessment and promotion of physical activity. The aim of this study was to determine the concurrent validity of various consumer activity monitor models and smartphone models for measuring steps. Methods : Participants completed three activity protocols: (1) overground walking with three different speeds (comfortable, slow, fast), (2) activities of daily living (ADLs) focusing on arm movements, and (3) intermittent walking. Participants wore 11 activity monitors (wrist: 8; hip: 2; ankle: 1) and four smartphones (hip: 3; calf: 1). Observed steps served as the criterion measure. The mean average percentage error (MAPE) was calculated for each device and protocol. Results : Eighteen healthy adults participated in the study (age: 28.8 ± 4.9 years). MAPEs ranged from 0.3–38.2% during overground walking, 48.2–861.2% during ADLs, and 11.2–47.3% during intermittent walking. Wrist-worn activity monitors tended to misclassify arm movements as steps. Smartphone data collected at the hip, analyzed with a separate algorithm, performed either equally or even superiorly to the research-grade ActiGraph. Conclusion : This study highlights the potential of smartphones for physical activity measurement. Measurement inaccuracies during intermittent walking and arm movements should be considered when interpreting study results and choosing activity monitors for evaluation purposes.

Suggested Citation

  • Verena Hartung & Mustafa Sarshar & Viktoria Karle & Layal Shammas & Asarnusch Rashid & Paul Roullier & Caroline Eilers & Mathias Mäurer & Peter Flachenecker & Klaus Pfeifer & Alexander Tallner, 2020. "Validity of Consumer Activity Monitors and an Algorithm Using Smartphone Data for Measuring Steps during Different Activity Types," IJERPH, MDPI, vol. 17(24), pages 1-16, December.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:24:p:9314-:d:461224
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    Cited by:

    1. Darcy Ummels & Emmylou Beekman & Susy M. Braun & Anna J. Beurskens, 2021. "Using an Activity Tracker in Healthcare: Experiences of Healthcare Professionals and Patients," IJERPH, MDPI, vol. 18(10), pages 1-19, May.

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