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Sensors (Basel, Switzerland)2022; 22(13); 4981; doi: 10.3390/s22134981

Detection of Horse Locomotion Modifications Due to Training with Inertial Measurement Units: A Proof-of-Concept.

Abstract: Detecting fatigue during training sessions would help riders and trainers to optimize their training. It has been shown that fatigue could affect movement patterns. Inertial measurement units (IMUs) are wearable sensors that measure linear accelerations and angular velocities, and can also provide orientation estimates. These sensors offer the possibility of a non-invasive and continuous monitoring of locomotion during training sessions. However, the indicators extracted from IMUs and their ability to show these locomotion changes are not known. The present study aims at defining which kinematic variables and indicators could highlight locomotion changes during a training session expected to be particularly demanding for the horses. Heart rate and lactatemia were measured to attest for the horse’s fatigue following the training session. Indicators derived from acceleration, angular velocities, and orientation estimates obtained from nine IMUs placed on 10 high-level dressage horses were compared before and after a training session using a non-parametric Wilcoxon paired test. These indicators were correlation coefficients (CC) and root mean square deviations (RMSD) comparing gait cycle kinematics measured before and after the training session and also movement smoothness estimates (SPARC, LDLJ). Heart rate and lactatemia measures did not attest to a significant physiological fatigue. However, the statistics show an effect of the training session (p < 0.05) on many CC and RMSD computed on the kinematic variables, indicating a change in the locomotion with the training session as well as on SPARCs indicators (p < 0.05), and revealing here a change in the movement smoothness both in canter and trot. IMUs seem then to be able to track locomotion pattern modifications due to training. Future research should be conducted to be able to fully attribute the modifications of these indicators to fatigue.
Publication Date: 2022-07-01 PubMed ID: 35808476PubMed Central: PMC9269723DOI: 10.3390/s22134981Google Scholar: Lookup
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  • Journal Article

Summary

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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

APA
Pasquiet B, Biau S, Trébot Q, Debril JF, Durand F, Fradet L. (2022). Detection of Horse Locomotion Modifications Due to Training with Inertial Measurement Units: A Proof-of-Concept. Sensors (Basel), 22(13), 4981. https://doi.org/10.3390/s22134981

Publication

ISSN: 1424-8220
NlmUniqueID: 101204366
Country: Switzerland
Language: English
Volume: 22
Issue: 13
PII: 4981

Researcher Affiliations

Pasquiet, Benoît
  • Plateau technique «Equitation et performance sportive», Institut français du cheval et de l'équitation, Avenue de l'École Nationale d'Équitation, 49411 Saumur, France.
Biau, Sophie
  • Plateau technique «Equitation et performance sportive», Institut français du cheval et de l'équitation, Avenue de l'École Nationale d'Équitation, 49411 Saumur, France.
Trébot, Quentin
  • Equipe Robotique, Biomécanique, Sport, Santé, Institut PPRIME, UPR3346 CNRS Université de Poitiers ENSMA, 86073 Poitiers, France.
Debril, Jean-François
  • Centre d'Analyse d'Image et Performance Sportive, CREPS de Poitiers, 86580 Vouneuil sous Biard, France.
Durand, François
  • Centre d'Analyse d'Image et Performance Sportive, CREPS de Poitiers, 86580 Vouneuil sous Biard, France.
Fradet, Laetitia
  • 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

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Citations

This article has been cited 2 times.
  1. Crecan CM, Peștean CP. Inertial Sensor Technologies-Their Role in Equine Gait Analysis, a Review.. Sensors (Basel) 2023 Jul 11;23(14).
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  2. 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).
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