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Animals
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Equine Gait Analysis: Translating Science into Practice
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Equine Gait Analysis: Translating Science into Practice

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Equids".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 43386

Special Issue Editors

Prof. Dr. Hilary M. Clayton

E-Mail Website
Guest Editor
College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA
Interests: equine locomotor biomechanics; rider-horse interaction; effects of tack and equipment on the horse; conditioning sport horses
Special Issues, Collections and Topics in MDPI journals
Dr. Lindsay St. George

E-Mail Website
Guest Editor
Research Centre for Applied Sport, Physical Activity and Performance, Faculty of Allied Health and Wellbeing, University of Central Lancashire, Preston, UK
Interests: equine biomechanics; equine muscle function during non-pathological and pathological gait; surface electromyography (sEMG); equine gait analysis

Special Issue Information

Dear Colleagues,

From ancient cave paintings to modern research labs, equine locomotion remains a source of fascination. The past half-century has seen what Professor René van Weeren described as the “Second Golden age of equine locomotion research”. Recent developments have been made possible by advances in computerization and micro-electronics and the development of lightweight, wireless sensors that have allowed equine gait analysis to migrate from the sophisticated research laboratory to the field. Researchers, veterinarians, and equestrians can now acquire high-quality data from horses in motion during clinical evaluations or athletic pursuits.

This message announces a Special Issue in the journal Animals entitled “Equine Gait Analysis: Translating Science into Practice”. This Special Issue is dedicated to covering the biomechanical analysis of horses. Authors are encouraged to submit manuscripts covering a broad spectrum of topics on equine locomotion including, but not limited to, clinical diagnostic and surveillance applications for lameness, field studies to evaluate and monitor athletic performance, and other novel areas of investigation. We hope you will consider submitting your latest research, a literature review, or an interesting case report for inclusion in this Special Issue.

Prof. Dr. Hilary M. Clayton
Dr. Lindsay St. George
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • horse
  • biomechanics
  • kinematics
  • kinetics
  • electromyography
  • equestrian sport
  • gaits
  • lameness

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Published Papers (10 papers)

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Research

14 pages, 2184 KiB  
Article
Asymmetry Thresholds Reflecting the Visual Assessment of Forelimb Lameness on Circles on a Hard Surface
by Claire Macaire, Sandrine Hanne-Poujade, Emeline De Azevedo, Jean-Marie Denoix, Virginie Coudry, Sandrine Jacquet, Lélia Bertoni, Amélie Tallaj, Fabrice Audigié, Chloé Hatrisse, Camille Hébert, Pauline Martin, Frédéric Marin and Henry Chateau
Animals 2023, 13(21), 3319; https://doi.org/10.3390/ani13213319 - 25 Oct 2023
Cited by 1 | Viewed by 1880
Abstract
The assessment of lameness in horses can be aided by objective gait analysis tools. Despite their key role of evaluating a horse at trot on a circle, asymmetry thresholds have not been determined for differentiating between sound and lame gait during this exercise. [...] Read more.
The assessment of lameness in horses can be aided by objective gait analysis tools. Despite their key role of evaluating a horse at trot on a circle, asymmetry thresholds have not been determined for differentiating between sound and lame gait during this exercise. These thresholds are essential to distinguish physiological asymmetry linked to the circle from pathological asymmetry linked to lameness. This study aims to determine the Asymmetry Indices (AIs) with the highest power to discriminate between a group of sound horses and a group of horses with consistent unilateral lameness across both circle directions, as categorized by visual lameness assessment conducted by specialist veterinarians. Then, thresholds were defined for the best performing AIs, based on the optimal sensitivity and specificity. AIs were calculated as the relative comparison between left and right minima, maxima, time between maxima and upward amplitudes of the vertical displacement of the head and the withers. Except the AI of maxima difference, the head AI showed the highest sensitivity (≥69%) and the highest specificity (≥81%) for inside forelimb lameness detection and the withers AI showed the highest sensitivity (≥72%) and the highest specificity (≥77%) for outside forelimb lameness detection on circles. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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17 pages, 1201 KiB  
Article
Visually Assessing Equine Quality of Movement: A Survey to Identify Key Movements and Patient-Specific Measures
by Annette G. Bowen, Gillian Tabor, Raphael Labens and Hayley Randle
Animals 2023, 13(18), 2822; https://doi.org/10.3390/ani13182822 - 5 Sep 2023
Cited by 1 | Viewed by 3312
Abstract
Outcome measures are essential for monitoring treatment efficacy. The lack of measures for quality of movement in equine physiotherapy and rehabilitation impairs evidence-based practice. To develop a new field-based outcome measure, it is necessary to determine movements most frequently observed during assessment of [...] Read more.
Outcome measures are essential for monitoring treatment efficacy. The lack of measures for quality of movement in equine physiotherapy and rehabilitation impairs evidence-based practice. To develop a new field-based outcome measure, it is necessary to determine movements most frequently observed during assessment of rehabilitation and performance management cases. An online survey of 81 equine sports medicine veterinarians and equine allied-health clinicians was conducted. The key movements identified included walk and trot on both firm and soft surfaces in a straight line and on a small circle, plus step back, hind leg cross-over, transitions and lunging at walk, trot and canter. The main barriers to observing some movements are access to suitable surfaces and the training level of the horse and handler. Subjective visual assessment of live or videoed horses was the most common method used to track progress of complex movements. The majority (82%) of survey participants agreed or strongly agreed that a modified Patient-Specific Functional Scale would be useful for measuring complex movements. Comments from all professions show a desire to have outcome measures relevant to their needs. This survey identified 24 in-hand movements, which can be used to form the foundation of a simple field-based outcome measure for quality of movement. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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13 pages, 2532 KiB  
Article
Saddle Thigh Block Design Can Influence Rider and Horse Biomechanics
by Rachel Murray, Mark Fisher, Vanessa Fairfax and Russell MacKechnie-Guire
Animals 2023, 13(13), 2127; https://doi.org/10.3390/ani13132127 - 27 Jun 2023
Viewed by 8147
Abstract
The association between rider–saddle interaction and horse kinematics has been little studied. It was hypothesized that differences in a thigh block design would influence (a) rider–saddle interface pressures, (b) rider kinematics, and (c) equine limb/spinal kinematics. Eighteen elite sport horses/riders were trotted using [...] Read more.
The association between rider–saddle interaction and horse kinematics has been little studied. It was hypothesized that differences in a thigh block design would influence (a) rider–saddle interface pressures, (b) rider kinematics, and (c) equine limb/spinal kinematics. Eighteen elite sport horses/riders were trotted using correctly fitted dressage saddles with thigh blocks S (vertical face) and F (deformable face). Contact area, mean, and peak pressure between rider and saddle were determined using an on-saddle pressure mat. Spherical markers allowed for the measurement of horse/rider kinematics using two-dimensional video analysis. The kinematics of the equine thoracolumbosacral spine were obtained using skin-mounted inertial measuring units. Results were compared between thigh blocks (paired t-test p ≤ 0.05). With F, the contact area, mean, and peak pressure between rider and saddle were significantly higher (p = 0.0001), and the rider trunk anterior tilt was reduced, indicating altered rider–saddle interaction. The horse thoracic axial rotation and flexion/extension were reduced (p = 0.01–0.03), caudal thoracic and lumbar lateral bend was increased (p = 0.02–0.04), and carpal flexion increased (p = 0.01–0.05) with F compared to S. During straight-line locomotion when in sitting trot, thigh block F was associated with altered rider–saddle interaction and rider and equine kinematics, leading to a more consistent rider–saddle interface, a more upright rider trunk during stance, an increased horse thoracic stability and lumbar lateral bend, and forelimb flexion, supporting the importance of optimising rider–saddle–horse interaction. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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17 pages, 2818 KiB  
Article
Effects of Jumping Phase, Leading Limb, and Arena Surface Type on Forelimb Hoof Movement
by Christina M. Rohlf, Tanya C. Garcia, Lyndsey J. Marsh, Elizabeth V. Acutt, Sarah S. le Jeune and Susan M. Stover
Animals 2023, 13(13), 2122; https://doi.org/10.3390/ani13132122 - 27 Jun 2023
Cited by 1 | Viewed by 1737
Abstract
During the stance phase of equine locomotion, ground reaction forces are exerted on the hoof, leading first to rapid deceleration (“braking”) and later to acceleration (“propulsion”) as the hoof leaves the ground. Excessive hoof deceleration has been identified as a risk factor for [...] Read more.
During the stance phase of equine locomotion, ground reaction forces are exerted on the hoof, leading first to rapid deceleration (“braking”) and later to acceleration (“propulsion”) as the hoof leaves the ground. Excessive hoof deceleration has been identified as a risk factor for musculoskeletal injury and may be influenced by arena surface properties. Therefore, our objective was to evaluate the effect of arena surface type (dirt, synthetic) on hoof translation of the leading and trailing forelimbs during jump takeoff and landing. Solar hoof angle, displacement, velocity, and deceleration were captured using kinematic markers and high-speed video for four horses jumping over a 1.1 m oxer at 12 different arenas (5 dirt, 7 synthetic). Surface vertical impact and horizontal shear properties were measured simultaneously. The effects of surface type (dirt, synthetic), jump phase (takeoff, landing), and limb (leading, trailing) on hoof movement were assessed using ANOVA (p < 0.05), while the relationships of hoof movement with surface mechanical properties were examined with correlation. Slide time (p = 0.032), horizontal velocity of the hoof (p < 0.001), and deceleration (p < 0.001) were greater in the leading limb, suggesting a higher risk of injury to the leading limb when braking. However, surface type and jump phase did not significantly affect deceleration during braking. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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18 pages, 4829 KiB  
Article
Electromyographic and Kinematic Comparison of the Leading and Trailing Fore- and Hindlimbs of Horses during Canter
by Lindsay B. St. George, Hilary M. Clayton, Jonathan K. Sinclair, Jim Richards, Serge H. Roy and Sarah Jane Hobbs
Animals 2023, 13(11), 1755; https://doi.org/10.3390/ani13111755 - 25 May 2023
Cited by 1 | Viewed by 1705
Abstract
This study compared muscle activity and movement between the leading (Ld) and trailing (Tr) fore- (F) and hindlimbs (H) of horses cantering overground. Three-dimensional kinematic and surface electromyography (sEMG) data were collected from right triceps brachii, biceps femoris, middle gluteal, and splenius from [...] Read more.
This study compared muscle activity and movement between the leading (Ld) and trailing (Tr) fore- (F) and hindlimbs (H) of horses cantering overground. Three-dimensional kinematic and surface electromyography (sEMG) data were collected from right triceps brachii, biceps femoris, middle gluteal, and splenius from 10 ridden horses during straight left- and right-lead canter. Statistical parametric mapping evaluated between-limb (LdF vs. TrF, LdH vs. TrH) differences in time- and amplitude-normalized sEMG and joint angle–time waveforms over the stride. Linear mixed models evaluated between-limb differences in discrete sEMG activation timings, average rectified values (ARV), and spatio-temporal kinematics. Significantly greater gluteal ARV and activity duration facilitated greater limb retraction, hip extension, and stifle flexion (p < 0.05) in the TrH during stance. Earlier splenius activation during the LdF movement cycle (p < 0.05), reflected bilateral activation during TrF/LdH diagonal stance, contributing to body pitching mechanisms in canter. Limb muscles were generally quiescent during swing, where significantly greater LdF/H protraction was observed through greater elbow and hip flexion (p < 0.05), respectively. Alterations in muscle activation facilitate different timing and movement cycles of the leading and trailing limbs, which justifies equal training on both canter leads to develop symmetry in muscular strength, enhance athletic performance, and mitigate overuse injury risks. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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44 pages, 8202 KiB  
Article
Is Markerless More or Less? Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture
by Felix Järemo Lawin, Anna Byström, Christoffer Roepstorff, Marie Rhodin, Mattias Almlöf, Mudith Silva, Pia Haubro Andersen, Hedvig Kjellström and Elin Hernlund
Animals 2023, 13(3), 390; https://doi.org/10.3390/ani13030390 - 24 Jan 2023
Cited by 12 | Viewed by 5827
Abstract
Computer vision is a subcategory of artificial intelligence focused on extraction of information from images and video. It provides a compelling new means for objective orthopaedic gait assessment in horses using accessible hardware, such as a smartphone, for markerless motion analysis. This study [...] Read more.
Computer vision is a subcategory of artificial intelligence focused on extraction of information from images and video. It provides a compelling new means for objective orthopaedic gait assessment in horses using accessible hardware, such as a smartphone, for markerless motion analysis. This study aimed to explore the lameness assessment capacity of a smartphone single camera (SC) markerless computer vision application by comparing measurements of the vertical motion of the head and pelvis to an optical motion capture multi-camera (MC) system using skin attached reflective markers. Twenty-five horses were recorded with a smartphone (60 Hz) and a 13 camera MC-system (200 Hz) while trotting two times back and forth on a 30 m runway. The smartphone video was processed using artificial neural networks detecting the horse’s direction, action and motion of body segments. After filtering, the vertical displacement curves from the head and pelvis were synchronised between systems using cross-correlation. This rendered 655 and 404 matching stride segmented curves for the head and pelvis respectively. From the stride segmented vertical displacement signals, differences between the two minima (MinDiff) and the two maxima (MaxDiff) respectively per stride were compared between the systems. Trial mean difference between systems was 2.2 mm (range 0.0–8.7 mm) for head and 2.2 mm (range 0.0–6.5 mm) for pelvis. Within-trial standard deviations ranged between 3.1–28.1 mm for MC and between 3.6–26.2 mm for SC. The ease of use and good agreement with MC indicate that the SC application is a promising tool for detecting clinically relevant levels of asymmetry in horses, enabling frequent and convenient gait monitoring over time. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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20 pages, 4000 KiB  
Article
Efficient Development of Gait Classification Models for Five-Gaited Horses Based on Mobile Phone Sensors
by Haraldur B. Davíðsson, Torben Rees, Marta Rut Ólafsdóttir and Hafsteinn Einarsson
Animals 2023, 13(1), 183; https://doi.org/10.3390/ani13010183 - 3 Jan 2023
Cited by 1 | Viewed by 3304
Abstract
Automated gait classification has traditionally been studied using horse-mounted sensors. However, smartphone-based sensors are more accessible, but the performance of gait classification models using data from such sensors has not been widely known or accessible. In this study, we performed horse gait classification [...] Read more.
Automated gait classification has traditionally been studied using horse-mounted sensors. However, smartphone-based sensors are more accessible, but the performance of gait classification models using data from such sensors has not been widely known or accessible. In this study, we performed horse gait classification using deep learning models and data from mobile phone sensors located in the rider’s pocket. We gathered data from 17 horses and 14 riders. The data were gathered simultaneously from movement sensors in a mobile phone located in the rider’s pocket and a gait classification system based on four wearable sensors attached to the horse’s limbs. With this efficient approach to acquire labelled data, we trained a Bi-LSTM model for gait classification. The only input to the model was a 50 Hz signal from the phone’s accelerometer and gyroscope that was rotated to the horse’s frame of reference. We demonstrate that sensor data from mobile phones can be used to classify the five gaits of the Icelandic horse with up to 94.4% accuracy. The result suggests that horse riding activities can be studied at a large scale using mobile phones to gather data on gaits. While our study showed that mobile phone sensors could be effective for gait classification, there are still some limitations that need to be addressed in future research. For example, further studies could explore the effects of different riding styles or equipment on gait classification accuracy or investigate ways to minimize the influence of factors such as phone placement. By addressing these questions, we can continue to improve our understanding of horse gait and its role in horse riding activities. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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14 pages, 2382 KiB  
Article
Investigation of Thresholds for Asymmetry Indices to Represent the Visual Assessment of Single Limb Lameness by Expert Veterinarians on Horses Trotting in a Straight Line
by Claire Macaire, Sandrine Hanne-Poujade, Emeline De Azevedo, Jean-Marie Denoix, Virginie Coudry, Sandrine Jacquet, Lélia Bertoni, Amélie Tallaj, Fabrice Audigié, Chloé Hatrisse, Camille Hébert, Pauline Martin, Frédéric Marin and Henry Chateau
Animals 2022, 12(24), 3498; https://doi.org/10.3390/ani12243498 - 11 Dec 2022
Cited by 9 | Viewed by 3595
Abstract
Defining whether a gait asymmetry should be considered as lameness is challenging. Gait analysis systems now provide relatively accurate objective data, but their interpretation remains complex. Thresholds for discriminating between horses that are visually assessed as being lame or sound, as well as [...] Read more.
Defining whether a gait asymmetry should be considered as lameness is challenging. Gait analysis systems now provide relatively accurate objective data, but their interpretation remains complex. Thresholds for discriminating between horses that are visually assessed as being lame or sound, as well as thresholds for locating the lame limb with precise sensitivity and specificity are essential for accurate interpretation of asymmetry measures. The goal of this study was to establish the thresholds of asymmetry indices having the best sensitivity and specificity to represent the visual single-limb lameness assessment made by expert veterinarians as part of their routine practice. Horses included in this study were evaluated for locomotor disorders at a clinic and equipped with the EQUISYM® system using inertial measurement unit (IMU) sensors. Visual evaluation by expert clinicians allocated horses into five groups: 49 sound, 62 left forelimb lame, 67 right forelimb lame, 23 left hindlimb lame, and 23 right hindlimb lame horses. 1/10 grade lame horses were excluded. Sensors placed on the head (_H), the withers (_W), and the pelvis (_P) provided vertical displacement. Relative difference of minimal (AI-min) and maximal (AI-max) altitudes, and of upward (AI-up) and downward (AI-down) amplitudes between right and left stance phases were calculated. Receiver operating characteristic (ROC) curves discriminating the sound horses from each lame limb group revealed the threshold of asymmetry indice associated with the best sensitivity and specificity. AI-up_W had the best ability to discriminate forelimb lame horses from sound horses with thresholds (left: −7%; right: +10%) whose sensitivity was greater than 84% and specificity greater than 88%. AI-up_P and AI-max_P discriminated hindlimb lame horses from sound horses with thresholds (left: −7%; right: +18% and left: −10%; right: +6%) whose sensitivity was greater than 78%, and specificity greater than 82%. Identified thresholds will enable the interpretation of quantitative data from lameness quantification systems. This study is mainly limited by the number of included horses and deserves further investigation with additional data, and similar studies on circles are warranted. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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15 pages, 1397 KiB  
Article
Locomotory Profiles in Thoroughbreds: Peak Stride Length and Frequency in Training and Association with Race Outcomes
by Charlotte Schrurs, Sarah Blott, Guillaume Dubois, Emmanuelle Van Erck-Westergren and David S. Gardner
Animals 2022, 12(23), 3269; https://doi.org/10.3390/ani12233269 - 24 Nov 2022
Cited by 6 | Viewed by 3756
Abstract
Racehorses competing in short (i.e., ‘sprinters’), middle- or longer-distance (i.e., ‘stayers’) flat races are assumed to have natural variation in locomotion; sprinters having an innately shorter stride than stayers. No study has objectively tested this theory. Here, racehorses (n = 421) were [...] Read more.
Racehorses competing in short (i.e., ‘sprinters’), middle- or longer-distance (i.e., ‘stayers’) flat races are assumed to have natural variation in locomotion; sprinters having an innately shorter stride than stayers. No study has objectively tested this theory. Here, racehorses (n = 421) were categorised as sprinters, milers or stayers based on known race distance (n = 3269 races). Stride parameters (peak length and frequency) of those racehorses were collected from prior race-pace training sessions on turf (n = 2689; ‘jumpout’, n = 1013), using a locomotion monitoring device. Pedigree information for all 421 racehorses was extracted to three-generations. In training, sprinters had a shorter stride of higher frequency and covered consecutive furlongs faster than stayers (p < 0.001). Relatively short or longer stride did not predict race success, but stayers had greater race success than sprinters (p < 0.001). Peak stride length and frequency were moderately heritable (h2 = 0.15 and 0.20, respectively). In conclusion, differences in stride were apparent between sprinters and stayers (e.g., shorter stride in sprinters) during routine training, even after accounting for their pedigree. Objective data on stride characteristics could supplement other less objectively obtained parameters to benefit trainers in the appropriate selection of races for each individual racehorse. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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20 pages, 781 KiB  
Article
Artificial Intelligence for Lameness Detection in Horses—A Preliminary Study
by Ann-Kristin Feuser, Stefan Gesell-May, Tobias Müller and Anna May
Animals 2022, 12(20), 2804; https://doi.org/10.3390/ani12202804 - 17 Oct 2022
Cited by 8 | Viewed by 6686
Abstract
Lameness in horses is a long-known issue influencing the welfare, as well as the use, of a horse. Nevertheless, the detection and classification of lameness mainly occurs on a subjective basis by the owner and the veterinarian. The aim of this study was [...] Read more.
Lameness in horses is a long-known issue influencing the welfare, as well as the use, of a horse. Nevertheless, the detection and classification of lameness mainly occurs on a subjective basis by the owner and the veterinarian. The aim of this study was the development of a lameness detection system based on pose estimation, which permits non-invasive and easily applicable gait analysis. The use of 58 reference points on easily detectable anatomical landmarks offers various possibilities for gait evaluation using a simple setup. For this study, three groups of horses were used: one training group, one analysis group of fore and hindlimb lame horses and a control group of sound horses. The first group was used to train the network; afterwards, horses with and without lameness were evaluated. The results show that forelimb lameness can be detected by visualising the trajectories of the reference points on the head and both forelimbs. In hindlimb lameness, the stifle showed promising results as a reference point, whereas the tuber coxae were deemed unsuitable as a reference point. The study presents a feasible application of pose estimation for lameness detection, but further development using a larger dataset is essential. Full article
(This article belongs to the Special Issue Equine Gait Analysis: Translating Science into Practice)
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