MURAL - Maynooth University Research Archive Library



    Squat Form Analysis using passive sensors and computer vision


    Share and Export

    McCormack, Sam and Meehan, Andrew (2023) Squat Form Analysis using passive sensors and computer vision. Project Report. UNSPECIFIED, Maynooth. (Unpublished)

    [thumbnail of AM_squat form analysis.pdf]
    Preview
     Text
    Available under License Creative Commons Attribution Non-commercial Share Alike.
    Download (1MB) | Preview

    Abstract

    Generatation of a program that can track and determine the repetitions and limb angles for the split squat exercise.
    Item Type: Monograph (Project Report)
    Additional Information: MU SPUR - Summer Programme for Undergraduate Research
    Keywords: Squat Form Analysis; passive sensors; computer vision;
    Academic Unit: Assisting Living & Learning,ALL institute
    Faculty of Science and Engineering > Electronic Engineering
    Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI
    Item ID: 21329
    Depositing User: Andrew Meehan
    Date Deposited: 20 Mar 2026 14:24
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Downloads

    Downloads per month over past year

    Origin of downloads

    Repository Staff Only (login required)

    Item control page
    Item control page
    MURAL - Maynooth University Research Archive Library is powered by EPrints 3.4 which is developed by the School of Electronics and Computer Science at the University of Southampton. About EPrints | Accessibility