Detection of Horse Locomotion Modifications Due to Training with Inertial Measurement Units: A Proof-of-Concept.
- Journal Article
Summary
This research focuses on using Inertial Measurement Units (IMUs), to detect modifications in horse locomotion due to fatigue from training and seeks to ascertain which indicators are most effective in monitoring these changes and the possibility of fatigue in horses.
Methodology and Variables
The researchers used IMUs, which are wearable devices that measure acceleration, angular velocities, and orientation estimates, offering a non-invasive, continuous monitoring system for gauging a horse’s movement during training. They were particularly keen on understanding if these devices were capable of identifying locomotion changes during a demanding training session. Notable variables involved in determining these changes included:
- Heart rate: to determine if the training session evokes physical fatigue on the horse.
- Lactatemia: to further assess physical fatigue post-training.
- Correlation coefficients (CC): to compare gait cycle kinematics before and after the training session.
- Root mean square deviations (RMSD): to determine changes in locomotion.
- Movement smoothness estimates (SPARC, LDLJ): to identify any variations in movement smoothness after the training session.
Testing Approach
Their examination was executed on 10 high-level dressage horses, where indicators derived from the aforementioned variables were compared before and after a demanding training session. To check for comparative changes in the variables, the researchers employed a non-parametric Wilcoxon paired test.
Results and Insights
While heart rate and lactatemia results did not indicate significant physiological fatigue post-training in horses, the computed CCs and RMSDs from kinematic variables demonstrated adjustments in horse locomotion. Training had also caused changes in movement smoothness, as shown by SPARC indicators. These changes were observed both in canter (a three-beat gait) and trot (a two-beat gait).
Future Research Direction
Although they concluded that IMUs can track locomotion pattern changes due to training, they called for further research. This is because it’s not definitively ascertained whether the detected modifications in indicators are purely due to fatigue. Therefore, future research should aim to directly link these indicator changes to horse fatigue to validate this monitoring method.
Cite This Article
Publication
Researcher Affiliations
- Plateau technique «Equitation et performance sportive», Institut français du cheval et de l'équitation, Avenue de l'École Nationale d'Équitation, 49411 Saumur, France.
- Plateau technique «Equitation et performance sportive», Institut français du cheval et de l'équitation, Avenue de l'École Nationale d'Équitation, 49411 Saumur, France.
- Equipe Robotique, Biomécanique, Sport, Santé, Institut PPRIME, UPR3346 CNRS Université de Poitiers ENSMA, 86073 Poitiers, France.
- Centre d'Analyse d'Image et Performance Sportive, CREPS de Poitiers, 86580 Vouneuil sous Biard, France.
- Centre d'Analyse d'Image et Performance Sportive, CREPS de Poitiers, 86580 Vouneuil sous Biard, France.
- Equipe Robotique, Biomécanique, Sport, Santé, Institut PPRIME, UPR3346 CNRS Université de Poitiers ENSMA, 86073 Poitiers, France.
MeSH Terms
- Acceleration
- Animals
- Biomechanical Phenomena
- Fatigue
- Gait / physiology
- Horses
- Locomotion / physiology
Grant Funding
- 2019 / Institut franu00e7ais du cheval et de l'u00e9quitation
Conflict of Interest Statement
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Citations
This article has been cited 2 times.- Crecan CM, Peștean CP. Inertial Sensor Technologies-Their Role in Equine Gait Analysis, a Review.. Sensors (Basel) 2023 Jul 11;23(14).
- Davíðsson HB, Rees T, Ólafsdóttir MR, Einarsson H. Efficient Development of Gait Classification Models for Five-Gaited Horses Based on Mobile Phone Sensors.. Animals (Basel) 2023 Jan 3;13(1).