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Recognition of Physiotherapeutic Exercises Through DTW and Low-Cost Vision-Based Motion Capture

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Advances in Human Factors and Systems Interaction (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 592))

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Abstract

Telemedicine is a current trend in healthcare. The present study is part of the ePHoRt project, which is a web-based platform for the rehabilitation of patients after hip replacement surgery. To be economically suitable the system is intended to be based on low-cost technologies, especially in terms of motion capture. This is the reason why the Kinect-based motion tracking is chosen. The paper focuses on the automatic assessment of the correctness of the exercises performed by the user. A Dynamic Time Warping (DTW) approach is used to discriminate between correct and incorrect movements. The classification of the movements through a Naïve Bayes classifier shows a very high percentage of accuracy (98.2%). Models are built for each individual and reeducation exercise with only few attributes and the same accuracy. Due to these promising results, the next step will consist of testing the algorithms on patients performing the exercises in real time.

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Authors and Affiliations

  1. Intelligent and Interactive Systems Lab (SI2 Lab), Universidad de Las Americas, Av. de los Granados E12-41 y Colimes esq., Quito, EC170125, Ecuador

    Yves Rybarczyk, Arián Aladro Gonzalo, Danilo Esparza, Mario Gonzalez & Santiago Villarreal

  2. Research Laboratory in Physiotherapy and Human Movement, Universidad de Las Americas, Av. de los Granados E12-41 y Colimes esq., Quito, EC170125, Ecuador

    Yves Rybarczyk, Arián Aladro Gonzalo, Danilo Esparza, Mario Gonzalez & Santiago Villarreal

  3. Department of Electrical Engineering, UNINOVA/CTS, Nova University of Lisbon, Lisbon, Portugal

    Yves Rybarczyk & Isabel L. Nunes

  4. Department of Mechanical and Industrial Engineering, UNIDEMI, Monte de Caparica, Portugal

    Yves Rybarczyk & Isabel L. Nunes

  5. University of Twente, Drienerlolaan 5, 7522 NB, Enschede, The Netherlands

    Jan Kleine Deters

  6. Pontificia Universidad Católica del Ecuador, Quito, Ecuador

    Danilo Esparza

Authors
  1. Yves Rybarczyk
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  2. Jan Kleine Deters
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  3. Arián Aladro Gonzalo
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  4. Danilo Esparza
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  5. Mario Gonzalez
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  6. Santiago Villarreal
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  7. Isabel L. Nunes
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Corresponding author

Correspondence to Yves Rybarczyk .

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Editors and Affiliations

  1. Dept Engg. Mecanica e Industrial, Universidade Nova de Lisboa, Caparica, Portugal

    Isabel L. Nunes

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Rybarczyk, Y. et al. (2018). Recognition of Physiotherapeutic Exercises Through DTW and Low-Cost Vision-Based Motion Capture. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2017. Advances in Intelligent Systems and Computing, vol 592. Springer, Cham. https://doi.org/10.1007/978-3-319-60366-7_33

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  • DOI: https://doi.org/10.1007/978-3-319-60366-7_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60365-0

  • Online ISBN: 978-3-319-60366-7

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