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A Data Set of Human Body Movements for Physical Rehabilitation Exercises

Author

Listed:
  • Aleksandar Vakanski

    (Industrial Technology, University of Idaho, 1776 Science Center Drive, Idaho Falls, ID 83402, USA
    These authors contributed equally to this work.)

  • Hyung-pil Jun

    (Department of Movement Sciences, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA
    These authors contributed equally to this work.)

  • David Paul

    (Department of Movement Sciences, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA
    These authors contributed equally to this work.)

  • Russell Baker

    (Department of Movement Sciences, University of Idaho, 875 Perimeter Drive, Moscow, ID 83844, USA
    These authors contributed equally to this work.)

Abstract

The article presents University of Idaho-Physical Rehabilitation Movement Data (UI-PRMD), a publically available data set of movements related to common exercises performed by patients in physical rehabilitation programs. For the data collection, 10 healthy subjects performed 10 repetitions of different physical therapy movements with a Vicon optical tracker and a Microsoft Kinect sensor used for the motion capturing. The data are in a format that includes positions and angles of full-body joints. The objective of the data set is to provide a basis for mathematical modeling of therapy movements, as well as for establishing performance metrics for evaluation of patient consistency in executing the prescribed rehabilitation exercises.

Suggested Citation

  • Aleksandar Vakanski & Hyung-pil Jun & David Paul & Russell Baker, 2018. "A Data Set of Human Body Movements for Physical Rehabilitation Exercises," Data, MDPI, vol. 3(1), pages 1-15, January.
    • Handle: RePEc:gam:jdataj:v:3:y:2018:i:1:p:2-:d:126342
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    Citations

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    Cited by:

    1. Alina Miron & Noureddin Sadawi & Waidah Ismail & Hafez Hussain & Crina Grosan, 2021. "IntelliRehabDS (IRDS)—A Dataset of Physical Rehabilitation Movements," Data, MDPI, vol. 6(5), pages 1-13, April.
    2. Simone Fiori & Andrea Vitali, 2019. "Statistical Modeling of Trivariate Static Systems: Isotonic Models," Data, MDPI, vol. 4(1), pages 1-29, January.

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