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A Novel Foot Progression Angle Detection Method

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Book cover Computer Vision in Control Systems-4

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 136))

Abstract

Foot Progression Angle (FPA) detection is an important measurement in clinical gait analysis. Currently, the FPA can only be computed, while walking in a laboratory with a marker-based or Initial Measure Unit (IMU) based motion capture systems. A novel Visual Feature Matching (VFM) method is presented here, measuring the FPA by comparing the shoe orientation with the progression, i.e. the walking direction. Both the foot orientation and progression direction are detected by image processing methods in rectified digital images. Differential FPA (DFPA) algorithm is developed to provide accurate FPA measurement. The hardware of this system combines only one wearable sensor, a chest or torso mounted smart phone camera, and a laptop on the same Wi-Fi network. There is no other prerequisite hardware installation or other specialized set up. This method is a solution for long-term gait self-monitoring in a home or community like environments. Our novel approach leads to simple and persistent, real time remote gait FPA monitoring, and it is a core of new bio-feedback medical procedure.

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Authors and Affiliations

  1. School of Engineering, RMIT University, GPO Box 2476, Melbourne, VIC, 3001, Australia

    Jeffery Young & Milan Simic

  2. Faculty of Health Sciences, University of Sydney, PO Box 170 Lidcombe, Sydney, NSW, 1825, Australia

    Milena Simic

Authors
  1. Jeffery Young
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  2. Milena Simic
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  3. Milan Simic
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Corresponding author

Correspondence to Jeffery Young .

Editor information

Editors and Affiliations

  1. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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© 2018 Springer International Publishing AG

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Young, J., Simic, M., Simic, M. (2018). A Novel Foot Progression Angle Detection Method. In: Favorskaya, M., Jain, L. (eds) Computer Vision in Control Systems-4. Intelligent Systems Reference Library, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-319-67994-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-67994-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67993-8

  • Online ISBN: 978-3-319-67994-5

  • eBook Packages: EngineeringEngineering (R0)

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