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Development and Validation of a New Method to Measure Walking Speed in Free-Living Environments Using the Actibelt® Platform

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  • Michaela Schimpl
  • Christian Lederer
  • Martin Daumer

Abstract

Walking speed is a fundamental indicator for human well-being. In a clinical setting, walking speed is typically measured by means of walking tests using different protocols. However, walking speed obtained in this way is unlikely to be representative of the conditions in a free-living environment. Recently, mobile accelerometry has opened up the possibility to extract walking speed from long-time observations in free-living individuals, but the validity of these measurements needs to be determined. In this investigation, we have developed algorithms for walking speed prediction based on 3D accelerometry data (actibelt®) and created a framework using a standardized data set with gold standard annotations to facilitate the validation and comparison of these algorithms. For this purpose 17 healthy subjects operated a newly developed mobile gold standard while walking/running on an indoor track. Subsequently, the validity of 12 candidate algorithms for walking speed prediction ranging from well-known simple approaches like combining step length with frequency to more sophisticated algorithms such as linear and non-linear models was assessed using statistical measures. As a result, a novel algorithm employing support vector regression was found to perform best with a concordance correlation coefficient of 0.93 (95%CI 0.92–0.94) and a coverage probability CP1 of 0.46 (95%CI 0.12–0.70) for a deviation of 0.1 m/s (CP2 0.78, CP3 0.94) when compared to the mobile gold standard while walking indoors. A smaller outdoor experiment confirmed those results with even better coverage probability. We conclude that walking speed thus obtained has the potential to help establish walking speed in free-living environments as a patient-oriented outcome measure.

Suggested Citation

  • Michaela Schimpl & Christian Lederer & Martin Daumer, 2011. "Development and Validation of a New Method to Measure Walking Speed in Free-Living Environments Using the Actibelt® Platform," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-12, August.
  • Handle: RePEc:plo:pone00:0023080
    DOI: 10.1371/journal.pone.0023080
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    Cited by:

    1. Danish A Ahmed & Ali R Ansari & Mudassar Imran & Kamal Dingle & Michael B Bonsall, 2021. "Mechanistic modelling of COVID-19 and the impact of lockdowns on a short-time scale," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-20, October.
    2. J P Stellmann & A Neuhaus & N Götze & S Briken & C Lederer & M Schimpl & C Heesen & M Daumer, 2015. "Ecological Validity of Walking Capacity Tests in Multiple Sclerosis," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-11, April.
    3. Nanna Notthoff & Johanna Drewelies & Paulina Kazanecka & Elisabeth Steinhagen-Thiessen & Kristina Norman & Sandra Düzel & Martin Daumer & Ulman Lindenberger & Ilja Demuth & Denis Gerstorf, 2018. "Feeling older, walking slower—but only if someone’s watching. Subjective age is associated with walking speed in the laboratory, but not in real life," European Journal of Ageing, Springer, vol. 15(4), pages 425-433, December.
    4. Hisashi Kawai & Shuichi Obuchi & Yutaka Watanabe & Hirohiko Hirano & Yoshinori Fujiwara & Kazushige Ihara & Hunkyung Kim & Yoshiyuki Kobayashi & Masaaki Mochimaru & Eiki Tsushima & Kozo Nakamura, 2020. "Association between Daily Living Walking Speed and Walking Speed in Laboratory Settings in Healthy Older Adults," IJERPH, MDPI, vol. 17(8), pages 1-10, April.
    5. Daniel L Belavý & Ulf Gast & Martin Daumer & Elena Fomina & Rainer Rawer & Hans Schießl & Stefan Schneider & Harald Schubert & Cristina Soaz & Dieter Felsenberg, 2013. "Progressive Adaptation in Physical Activity and Neuromuscular Performance during 520d Confinement," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-7, March.

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