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Equine veterinary journal. Supplement2007; (36); 400-405; doi: 10.1111/j.2042-3306.2006.tb05576.x

A pattern recognition approach for the quantification of horse and rider interactions.

Abstract: Interactions of various systems were investigated in several studies of dynamic systems, but the interactions between horse and rider have not yet been documented. These interactions include the rider's ability to control the horse, adapt to the horse and maintain both participants' body position. An optimum interaction is also adapted to the individual nature of the horse. Objective: To identify rider-horse interactions by means of artificial neural nets analysing the time-continuous pattern. Methods: Fourteen horses were measured trotting on hand, and ridden at working trot with a professional and a recreational rider using a 3D high speed video system (120 Hz)1. Angles were calculated after low pass filtering (5-20 Hz). Horse movements were described by 2D angles, angular velocities, and angular accelerations of variables of the right body side: hind and front fetlock, head, back and the summation angle of carpus, elbow, and shoulder, the summation angle of hock, stifle, and hip. Distances between the trajectories of the feature vectors in an N = 11 x 11 Kohonen map were determined and analysed by means of a cluster analysis. Results: Depending on the variables included, both rider specific as well as horse specific movement patterns could be identified. The time courses of the head angle indicate a movement pattern mainly dominated by the rider, whereas the time courses of variables of the hind fetlock and hock in most cases did not show differences between the conditions with, and without, rider. The skill of the professional rider could be documented with a higher adaptation to the horse's movement pattern. Conclusions: The presented time course oriented approach provides a sensitive tool in order to quantify the interaction of rider and horse.
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Publication Date: 2007-04-04 PubMed ID: 17402455DOI: 10.1111/j.2042-3306.2006.tb05576.xGoogle Scholar: Lookup
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  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research article involves an investigation into the interactions between horses and riders using a pattern recognition approach. Using artificial neural networks, the study aimed to identify and quantify these interactions for a more objective understanding of the dynamic relationship between the horse and rider.

Objective and Methodology

  • The study’s objective was to investigate the interactions between a rider and a horse, particularly focusing on rider’s ability to control the horse, adapt to the horse, and maintain body position for both participants.
  • The researchers used artificial neural networks to analyze the patterns in the time-continuous interactions between the rider and the horse.
  • A sample of 14 horses was taken, and their movements were measured while trotting on hand and while being ridden at a working trot by both a professional and a recreational rider.
  • The researchers used a 3D high speed video system to capture the movements at 120 Hz, and angles were calculated after low pass filtering.
  • Various parameters such as 2D angles, angular velocities, and angular accelerations of variables like hind and front fetlock, head, back, summation angle of carpus etc. were measured to describe the horse movements.
  • A mathematical technique – Kohonen map, was employed to determine the distance between the trajectories of the feature vectors. These were then analyzed using cluster analysis.

Results

  • The findings from this research indicated that unique, identifiable movement patterns exist both specific to different riders and horses.
  • Time course of the head angle indicated a movement pattern that was primarily dominated by the rider’s actions.
  • In contrast, variables like the hind fetlock and hock didn’t show any considerable difference between conditions with or without the rider.
  • The professional rider demonstrated higher adaptation to the horse’s movement pattern than the recreational rider.

Conclusion

  • This study, using a time-course oriented approach, presents a sensitive tool to quantify the interaction of rider and horse, providing new insights into the dynamics of this relationship.
  • The results can be valuable in enhancing the effectiveness of the training process, improving the performance of professional riders, and facilitating animal welfare.

Cite This Article

APA
Schöllhorn WI, Peham C, Licka T, Scheidl M. (2007). A pattern recognition approach for the quantification of horse and rider interactions. Equine Vet J Suppl(36), 400-405. https://doi.org/10.1111/j.2042-3306.2006.tb05576.x

Publication

Equine veterinary journal. Supplement
NlmUniqueID: 9614088
Country: United States
Language: English
Issue: 36
Pages: 400-405

Researcher Affiliations

Schöllhorn, W I
  • Faculty for Psychology and Sport Science, University of Muenster, Horstmarer Landweg 62b, 41849 Muenster, Germany; and tUniversity of Veterinary Medicine, Vienna, Austria.
Peham, C
    Licka, T
      Scheidl, M

        MeSH Terms

        • Animals
        • Biomechanical Phenomena
        • Cluster Analysis
        • Gait / physiology
        • Horses / physiology
        • Humans
        • Imaging, Three-Dimensional / veterinary
        • Physical Conditioning, Animal / physiology
        • Stress, Mechanical
        • Video Recording
        • Weight-Bearing / physiology

        Citations

        This article has been cited 15 times.
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