Implementation and validity of the long jump knowledge-based system: Case of the approach run phase

Teerawat Kamnardsiri; Worawit Janchai; Pattaraporn Khuwuthyakorn; Wacharee Rittiwat

doi:10.7287/peerj.preprints.27524v1

Implementation and validity of the long jump knowledge-based system: Case of the approach run phase

Teerawat Kamnardsiri ¹, Worawit Janchai¹, Pattaraporn Khuwuthyakorn¹, Wacharee Rittiwat²

1 College of Arts, Media and Technology, Chiang Mai University, Muang, Chiamg Mai, Thailand

2 Faculty of Physical Education, Srinakharinwirot University, Sukhumvit, Bangkok, Thailand

DOI: 10.7287/peerj.preprints.27524v1

Published: 2019-02-08
Accepted: 2019-02-08

Subject Areas: Bioinformatics, Autonomous Systems, Computer Vision, Emerging Technologies, Graphics
Keywords: video analysis, maximum speed detection, knowledge-based system, long jump biomechanics, image processing, computer vision

Copyright: © 2019 Kamnardsiri et al.
Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.

Cite this article: Kamnardsiri T, Janchai W, Khuwuthyakorn P, Rittiwat W. 2019. Implementation and validity of the long jump knowledge-based system: Case of the approach run phase. PeerJ Preprints 7:e27524v1 https://doi.org/10.7287/peerj.preprints.27524v1

Abstract

This study aimed to propose the method of implementation of the Knowledge-Based System (KBS) in the case of approach-run phase. The proposed method was implemented for improving the long jump performance of athletes in the approach-run phase. Moreover, this study aimed to examine KBS concurrent validity in distinguishing between professional and amateur populations and then KBS convergent validity against a Tracker video analysis tool. Seven running professionals aged 19 to 42 years and five amateurs aged 18 to 38 years had captured with ten conditions of different movements (C1 to C10) using a standard video camera (60 fps, 10 mm lens). The camera was fixed on the tripod. The results showing an age-related difference in a speed measurement of ten conditions were evidently using the KBS. Good associations were found between KBS and Tracker 4.94 video analysis tool across various conditions of three variables that were the starting position (r=0.926 and 0.963), the maximum velocity (r=0.972 and 0.995) and the location of maximum velocity (r=0.574 and 0.919). In conclusion, the proposed method is a reliable tool for measuring the starting position, maximum speed and position of maximum speed. Furthermore, the proposed method can also distinguish speed performance between professional and amateur across multiple movement conditions.