IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v3y2018i1p2-d126342.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/3/1/2/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/3/1/2/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simone Fiori & Andrea Vitali, 2019. "Statistical Modeling of Trivariate Static Systems: Isotonic Models," Data, MDPI, vol. 4(1), pages 1-29, January.
    2. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:3:y:2018:i:1:p:2-:d:126342. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.