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Quadrupedal Gait Analysis in the Field

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 15 July 2025 | Viewed by 2760

Special Issue Editor


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Guest Editor
Faculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada
Interests: biomechanics; gait analysis; inertial sensors; quadrupedal; animals; IMUs, GPS/GNSS and optical setups

Special Issue Information

Dear Colleagues,

An ever-increasing number of sensor devices and smartphone apps are emerging for the quantification of gait parameters in quadrupedal animals, with a particular focus on horses, amidst the heightened awareness of welfare-related topics in the context of equestrian sports and performance. With the advent of artificial intelligence-driven analysis and sensor use during racing and FEI-regulated equestrian sports, there comes the need to better understand how different tools and methods are working and which biomechanical parameters can be measured with precision.

As an applied example of quadrupedal gait analysis in the field, in clinical practice, e.g., used by veterinarians or animal musculoskeletal practitioners or hoof care providers, quantitative measurements can aid in evidence-based decision-making or enable the move from a reactive paradigm of detecting impairments to a pro-active, preventative paradigm implementing long-term monitoring and performance optimization while minimizing injury risk.

With this Special Issue, we invite contributions about quantitative measurements of animal movement ‘in the field’.

Prof. Dr. Thilo Pfau
Guest Editor

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Keywords

  • quadrupedal gait analysis
  • sensor technology
  • musculoskeletal injury reduction
  • performance optimisation
  • quantitative measurements in field applications

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Published Papers (2 papers)

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Research

14 pages, 542 KiB  
Article
Discrimination of the Lame Limb in Horses Using a Machine Learning Method (Support Vector Machine) Based on Asymmetry Indices Measured by the EQUISYM System
by Emma Poizat, Mahaut Gérard, Claire Macaire, Emeline De Azevedo, Jean-Marie Denoix, Virginie Coudry, Sandrine Jacquet, Lélia Bertoni, Amélie Tallaj, Fabrice Audigié, Chloé Hatrisse, Camille Hébert, Pauline Martin, Frédéric Marin, Sandrine Hanne-Poujade and Henry Chateau
Sensors 2025, 25(4), 1095; https://doi.org/10.3390/s25041095 - 12 Feb 2025
Cited by 1 | Viewed by 819
Abstract
Lameness detection in horses is a critical challenge in equine veterinary practice, particularly when symptoms are mild. This study aimed to develop a predictive system using a support vector machine (SVM) to identify the affected limb in horses trotting in a straight line. [...] Read more.
Lameness detection in horses is a critical challenge in equine veterinary practice, particularly when symptoms are mild. This study aimed to develop a predictive system using a support vector machine (SVM) to identify the affected limb in horses trotting in a straight line. The system analyzed data from inertial measurement units (IMUs) placed on the horse’s head, withers, and pelvis, using variables such as vertical displacement and retraction angles. A total of 287 horses were included, with 256 showing single-limb lameness and 31 classified as sound. The model achieved an overall accuracy of 86%, with the highest success rates in identifying right and left forelimb lameness. However, there were challenges in identifying sound horses, with a 54.8% accuracy rate, and misclassification between forelimb and hindlimb lameness occurred in some cases. The study highlighted the importance of specific variables, such as vertical head and withers displacement, for accurate classification. Future research should focus on refining the model, exploring deep learning methods, and reducing the number of sensors required, with the goal of integrating these systems into equestrian equipment for early detection of locomotor issues. Full article
(This article belongs to the Special Issue Quadrupedal Gait Analysis in the Field)
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13 pages, 584 KiB  
Article
Inertial Sensor-Based Quantification of Movement Symmetry in Trotting Warmblood Show-Jumping Horses after “Limb-by-Limb” Re-Shoeing of Forelimbs with Rolled Rocker Shoes
by Craig Bark, Patrick Reilly, Renate Weller and Thilo Pfau
Sensors 2024, 24(15), 4848; https://doi.org/10.3390/s24154848 - 25 Jul 2024
Viewed by 1380
Abstract
Hoof care providers are pivotal for implementing biomechanical optimizations of the musculoskeletal system in the horse. Regular visits allow for the collection of longitudinal, quantitative information (“normal ranges”). Changes in movement symmetry, e.g., after shoeing, are indicative of alterations in weight-bearing and push-off [...] Read more.
Hoof care providers are pivotal for implementing biomechanical optimizations of the musculoskeletal system in the horse. Regular visits allow for the collection of longitudinal, quantitative information (“normal ranges”). Changes in movement symmetry, e.g., after shoeing, are indicative of alterations in weight-bearing and push-off force production. Ten Warmblood show jumping horses (7–13 years; 7 geldings, 3 mares) underwent forelimb re-shoeing with rolled rocker shoes, one limb at a time (“limb-by-limb”). Movement symmetry was measured with inertial sensors attached to the head, withers, and pelvis during straight-line trot and lunging. Normalized differences pre/post re-shoeing were compared to published test–retest repeatability values. Mixed-model analysis with random factors horse and limb within horse and fixed factors surface and exercise direction evaluated movement symmetry changes (p < 0.05, Bonferroni correction). Withers movement indicated increased forelimb push-off with the re-shod limb on the inside of the circle and reduced weight-bearing with the re-shod limb and the ipsilateral hind limb on hard ground compared to soft ground. Movement symmetry measurements indicate that a rolled rocker shoe allows for increased push-off on soft ground in trot in a circle. Similar studies should study different types of shoes for improved practically relevant knowledge about shoeing mechanics, working towards evidence-based preventative shoeing. Full article
(This article belongs to the Special Issue Quadrupedal Gait Analysis in the Field)
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