Title | ||
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Identifying patterns in trunk/head/elbow changes of riders and non-riders: A cluster analysis approach |
Abstract | ||
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Correct rider oscillation and position are the basics for a good horseback riding performance. In this paper, we propose a framework for the automatic analysis of athletes behaviour based on cluster analysis. Two groups of athletes (riders vs non-riders) were assigned to a horseback riding simulator exercise. The participants exercised four different incremental horse oscillation frequencies. This paper studies the postural coordination, by computing the different discrete relative phases of head-horse, elbow-horse and trunk-horse oscillations. Two clustering algorithms are then applied to automatically identify the change of rider and non-rider behaviour in terms of postural coordination. The results showed that the postural coordination was influenced by the level of rider expertise. More diverse behaviour was observed for non-riders. At the opposite, riders produced lower postural displacements and deployed more efficient postural control. The postural coordination for both groups was also influenced by the oscillation frequencies. |
Year | DOI | Venue |
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2022 | 10.1016/j.compbiomed.2021.105193 | COMPUTERS IN BIOLOGY AND MEDICINE |
Keywords | DocType | Volume |
Cluster analysis, Discrete relative phase, Mechanical horse, Postural coordination, Sport | Journal | 143 |
ISSN | Citations | PageRank |
0010-4825 | 0 | 0.34 |
References | Authors | |
0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Imen Trabelsi | 1 | 0 | 0.34 |
Romain Hérault | 2 | 0 | 0.34 |
Héloise Baillet | 3 | 0 | 0.34 |
Régis Thouvarecq | 4 | 0 | 0.34 |
Ludovic Seifert | 5 | 0 | 1.35 |
Gilles Gasso | 6 | 0 | 0.34 |