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International Conference on Information and Communication Technologies for Ageing Well and e-Health

ICT4AWE 2018: Information and Communication Technologies for Ageing Well and e-Health pp 126–141Cite as

Vision-Based Marker-Less Spatiotemporal Gait Analysis by Using a Mobile Platform: Preliminary Validation

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 982))

Abstract

Gait analysis is one of the most useful tools for assessing age-related conditions. This study describes the preliminary validation of a novel vision-based method for unobtrusive, ambulatory monitoring of spatiotemporal gait parameters. The method uses a mobile platform that is equipped with a Microsoft Kinect. A proprietary, generative tracker is used for measuring the 3D segmental movement of the subject. A novel method was developed for extracting gait parameters from the raw joint measurements by using the relative distance between the two ankle joints. The results are assessed in terms of mean absolute error and mean absolute percentage error with respect to a motion capture system. The mean absolute error ± precision was 5.5 ± 3.5 cm for stride length, 1.7 ± 1.3 cm for step width, 0.93 ± 0.44 steps/min for cadence, and 2.5 ± 2.0% for single limb support. While these results are promising, additional experiments are required to assess the repeatability of this approach.

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Acknowledgements

The authors would like to thank MALL (Movements posture & Analysis Laboratory Leuven) of the Faculty of Movement and Rehabilitation Sciences Leuven for providing the facility equipped with a VICON motion capture system in order to validate the proposed platform. Robin Amsters is an SB fellow of the Research Foundation Flanders (FWO) under grant agreement 1S57718N.

Author information

Authors and Affiliations

  1. eMedia Research Lab, KU Leuven, 3000, Leuven, Belgium

    Benjamin Filtjens & Bart Vanrumste

  2. Intelligent Mobile Platform Research Group, KU Leuven, 3000, Leuven, Belgium

    Benjamin Filtjens, Robin Amsters, Ali Bin Junaid & Peter Slaets

  3. Human Movement Biomechanics Research Group, KU Leuven, 3001, Heverlee, Belgium

    Benedicte Vanwanseele

  4. Department of Electrical Engineering (ESAT), STADIUS - IMEC, KU Leuven, 3001, Heverlee, Belgium

    Bart Vanrumste

  5. Department of Mechanical Engineering, KU Leuven, 3001, Heverlee, Belgium

    Benjamin Filtjens, Robin Amsters, Ali Bin Junaid, Nick Damen, Jeroen Van De Laer & Peter Slaets

  6. Department of Movement Sciences, KU Leuven, 3001, Heverlee, Belgium

    Benedicte Vanwanseele

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  1. Benjamin Filtjens
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  2. Robin Amsters
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  3. Ali Bin Junaid
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  4. Nick Damen
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  5. Jeroen Van De Laer
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  6. Benedicte Vanwanseele
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  8. Peter Slaets
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Corresponding author

Correspondence to Benjamin Filtjens .

Editor information

Editors and Affiliations

  1. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Panagiotis D. Bamidis

  2. Institut für Psychologie, RWTH Aachen University, Aachen, Nordrhein-Westfalen, Germany

    Martina Ziefle

  3. Wrocław University of Economics, Institute of Business Informatics, Wrocław, Poland

    Leszek A. Maciaszek

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Filtjens, B. et al. (2019). Vision-Based Marker-Less Spatiotemporal Gait Analysis by Using a Mobile Platform: Preliminary Validation. In: Bamidis, P., Ziefle, M., Maciaszek, L. (eds) Information and Communication Technologies for Ageing Well and e-Health. ICT4AWE 2018. Communications in Computer and Information Science, vol 982. Springer, Cham. https://doi.org/10.1007/978-3-030-15736-4_7

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  • DOI: https://doi.org/10.1007/978-3-030-15736-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15735-7

  • Online ISBN: 978-3-030-15736-4

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