IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/5624482.html
   My bibliography  Save this article

Intelligent Analysis and Evaluation Method of Athletics Running Data Based on Big Data Statistical Model

Author

Listed:
  • Yushan Ge
  • Hangjun Che

Abstract

To investigate the effectiveness of pedometry in athletics at different running speeds and on different walking surfaces, and to test whether it can be used for running for fitness and for pedometry on hardened concrete surfaces in daily life. The steps were measured under laboratory conditions using a running platform at 5 min at 5 speeds of 3.2 km/h, 4.8 km/h, 6.4 km/h, 8.0 km/h, and 9.6 km/h (actual steps were accurately determined by video playback), followed by 300 steps each at low, normal and fast speeds on an outdoor plastic athletics track. There were significant differences between the smart bracelet and the mobile phone sports app at low running speeds on four different surfaces: outdoor plastic track, dirt, concrete and mountainous terrain. The difference was not significant in normal pace and fast walking.

Suggested Citation

  • Yushan Ge & Hangjun Che, 2022. "Intelligent Analysis and Evaluation Method of Athletics Running Data Based on Big Data Statistical Model," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, March.
    • Handle: RePEc:hin:jnlmpe:5624482
    DOI: 10.1155/2022/5624482
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/5624482.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2022/5624482.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/5624482?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnlmpe:5624482. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.