A method to optimize a typology-based classification system
Schnitzler, C., Croft, J., Button, C., Ulmers, M., & Davids, K. (2014). A method to optimize a typology-based classification system. In D. James (Ed.), The 2014 conference of the International Sports Engineering Association (ISEA 2014) (pp. 9-13). Elsevier BV. Procedia Engineering, 72. https://doi.org/10.1016/j.proeng.2014.06.003
Julkaistu sarjassa
Procedia EngineeringToimittajat
Päivämäärä
2014Tekijänoikeudet
© 2014 Elsevier Ltd. Open access under CC BY-NC-ND license. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work in properly cited. The Creative Commons Public Domain Dedication waiver applies to the data made available in this article, unless otherwise stated.
This study sought to provide guidelines for implementing typology-based qualitative analysis of human movement patterns.Fifteen participant-analysts were instructed how to classify treading water behaviours into eight different categories using a
training set of videos. They were later provided with two additional sets of videos called validation, and test sets. Results first identified reliable (n=9), and not reliable (n=6) analysts. A decision study outlined that one analyst was sufficient to reliably
categorize the behaviours in the ‘reliable’ analyst group, whereas up to four were necessary in the ‘unreliable’ group. These data provided new insights into more objective qualitative analysis methods for understanding human movement behaviours.
Julkaisija
Elsevier BVKonferenssi
Engineering of SportKuuluu julkaisuun
The 2014 conference of the International Sports Engineering Association (ISEA 2014)ISSN Hae Julkaisufoorumista
1877-7058Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/23995965
Metadata
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Lisenssi
Ellei muuten mainita, aineiston lisenssi on © 2014 Elsevier Ltd. Open access under CC BY-NC-ND license. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work in properly cited. The Creative Commons Public Domain Dedication waiver applies to the data made available in this article, unless otherwise stated.
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