Variation in frontal plane joint angles in horses

Unt, V. E.; Evans, John H.; Reed, S. R.; Pfau, Thilo; Weller, R.

doi:10.1111/j.2042-3306.2010.00192.x

Cited by 6 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Inter-horse variation was higher than intra-horse variations, supporting the findings from other kinematic studies (Cano et al, 2001;Clayton et al, 2007b;Unt et al, 2010). For both the PIPJ and the DIPJ measurements, there was a higher variation at trot compared with walk.…”

Section: Discussionsupporting

confidence: 86%

Sagittal distal limb kinematics inside the hoof capsule captured using high-speed fluoroscopy in walking and trotting horses

Roach

Pfau

Bryars

et al. 2014

The Veterinary Journal

Self Cite

View full text Add to dashboard Cite

Section: Discussionsupporting

confidence: 86%

Sagittal distal limb kinematics inside the hoof capsule captured using high-speed fluoroscopy in walking and trotting horses

Roach

Pfau

Bryars

et al. 2014

The Veterinary Journal

Self Cite

View full text Add to dashboard Cite

“…The only condition for which there was a difference between whole limb angle and MCIII angle was for the inside limb on a curve, with whole limb angle 1.9˚greater than MCIII angle. Thoroughbreds typically show a mild carpal valgus of 5.8˚standing and 5.3˚when walking [33], but no conformational measurements were made in this study. However, as no differences were seen between whole limb and MCIII angle for other circumstances, it is reasonable to suggest that this difference is due to asymmetric loading about the long axis of the limb during curve running.…”

Section: Plos Onementioning

confidence: 95%

The effect of curve running on distal limb kinematics in the Thoroughbred racehorse

et al. 2020

View full text Add to dashboard Cite

During racing, injury is more likely to occur on a bend than on a straight segment of track. This study aimed to quantify the effects of galloping at training speeds on large radius curves on stride parameters and limb lean angle in order to assess estimated consequences for limb loading. Seven Thoroughbred horses were equipped with a sacrum-mounted inertial measurement unit with an integrated GPS, two hoof-mounted accelerometers and retro-reflective markers on the forelimbs. Horses galloped 2–4 circuits anticlockwise around an oval track and were filmed at 120 frames per second using an array of ten cameras. Speed and curve radius were derived from GPS data and used to estimate the centripetal acceleration necessary to navigate the curve. Stride, stance and swing durations and duty factor (DF) were derived from accelerometer data. Limb markers were tracked and whole limb and third metacarpus (MCIII) angles were calculated. Data were analysed using mixed effects models with a significance level of p < 0.05. For horses galloping on the correct lead, DF was higher for the inside (lead) leg on the straight and on the curve. For horses galloping on the incorrect lead, there was no difference in DF between inside and outside legs on the straight or on the curve. DF decreased by 0.61% of DF with each 1 m s-2 increase in centripetal acceleration (p < 0.001). Whole limb inclination angle increased by 1.5° per 1 m s-1 increase in speed (p = 0.002). Limb lean angles increase as predicted, and lead limb function mirrors the functional requirements for curve running. A more comprehensive understanding of the effects of lean and torque on the distal limb is required to understand injury mechanisms.

show abstract

“…In the equine veterinary field, motion capture has demonstrated its potential in clinic applications for lameness diagnostics 46,47 . However, within this field, the focus is often limited to capture of locomotion data from a limited number of anatomical landmarks [48][49][50] due to difficulty and time constrain in placing markers on the horse's body. This may lead to less analysis and a lesser understanding of full-body motions.…”

Section: Background and Summarymentioning

confidence: 99%

The Poses for Equine Research Dataset (PFERD)

Li,

Mellbin,

Krogager

et al. 2024

Sci Data

View full text Add to dashboard Cite

Studies of quadruped animal motion help us to identify diseases, understand behavior and unravel the mechanics behind gaits in animals. The horse is likely the best-studied animal in this aspect, but data capture is challenging and time-consuming. Computer vision techniques improve animal motion extraction, but the development relies on reference datasets, which are scarce, not open-access and often provide data from only a few anatomical landmarks. Addressing this data gap, we introduce PFERD, a video and 3D marker motion dataset from horses using a full-body set-up of densely placed over 100 skin-attached markers and synchronized videos from ten camera angles. Five horses of diverse conformations provide data for various motions from basic poses (eg. walking, trotting) to advanced motions (eg. rearing, kicking). We further express the 3D motions with current techniques and a 3D parameterized model, the hSMAL model, establishing a baseline for 3D horse markerless motion capture. PFERD enables advanced biomechanical studies and provides a resource of ground truth data for the methodological development of markerless motion capture.

show abstract

Variation in frontal plane joint angles in horses

Abstract: SummaryReasons for performing study: Conformation in horses is often considered an indicator of athletic ability, performance and resistance to orthopaedic disease. Evaluation is performed in the standing horse and repeatability influenced by stance.

Cited by 6 publications

References 30 publications

Sagittal distal limb kinematics inside the hoof capsule captured using high-speed fluoroscopy in walking and trotting horses

Sagittal distal limb kinematics inside the hoof capsule captured using high-speed fluoroscopy in walking and trotting horses

The effect of curve running on distal limb kinematics in the Thoroughbred racehorse

The Poses for Equine Research Dataset (PFERD)

Contact Info

Product

Resources

About