In this paper, we describe and validate the EquiMoves system, which aims to support equine veterinarians in assessing lameness and gait performance in horses. The system works by capturing horse motion from up to eight synchronized wireless inertial measurement units. It can be used in various equine gait modes, and analyzes both upper-body and limb movements. The validation against an optical motion capture system is based on a Bland–Altman analysis that illustrates the agreement between the two systems. The sagittal kinematic results (protraction, retraction, and sagittal range of motion) show limits of agreement of ±2.3 degrees and an absolute bias of 0.3 degrees in the worst case. The coronal kinematic results (adduction, abduction, and coronal range of motion) show limits of agreement of −8.8 and 8.1 degrees, and an absolute bias of 0.4 degrees in the worst case. The worse coronal kinematic results are most likely caused by the optical system setup (depth perception difficulty and suboptimal marker placement). The upper-body symmetry results show no significant bias in the agreement between the two systems; in most cases, the agreement is within ±5 mm. On a trial-level basis, the limits of agreement for withers and sacrum are within ±2 mm, meaning that the system can properly quantify motion asymmetry. Overall, the bias for all symmetry-related results is less than 1 mm, which is important for reproducibility and further comparison to other systems.

Quantitative gait analysis has the potential to offer objective and unbiased gait information that can assist clinical decision-making. In recent years, a growing number of gait analysis systems have come onto the market, highlighting the demand for such technology in equine orthopaedics. However, it is imperative that the measured variables which are used as outcome parameters are supported by scientific evidence and that the interpretation of such measurements is backed by a proper understanding of the biomechanical principles of equine locomotion. This review, which is based on studies on experimentally induced lameness, summarises the currently most widely used methods for gait analysis and the available evidence concerning gait parameters that can be used to quantify gait changes due to lameness. These are discussed regarding their current and future potential for routine clinical application.

SummaryBackgroundThe main criteria for lameness assessment in horses are head movement for forelimb lameness and pelvic movement for hindlimb lameness. However, compensatory head nod in horses with primary hindlimb lameness is a well‐known phenomenon. This compensatory head nod movement can be easily misinterpreted as a sign of primary ipsilateral forelimb lameness. Therefore, discriminating compensatory asymmetries from primary directly pain‐related movement asymmetries is a prerequisite for successful lameness assessment.ObjectivesTo investigate the association between head, withers and pelvis movement asymmetry in horses with induced forelimb and hindlimb lameness.Study designExperimental study.MethodsIn 10 clinically sound Warmblood riding horses, forelimb and hindlimb lameness were induced using a sole pressure model. The horses were then trotted on a treadmill. Three‐dimensional optical motion capture was used to collect kinematic data from reflective markers attached to the poll, withers and tubera sacrale. The magnitude and side (left or right) of the following symmetry parameters, vertical difference in minimum position, maximum position and range‐up were calculated for head, withers, and pelvis. Mixed models were used to analyse data from induced forelimb and hindlimb lameness.ResultsFor each mm increase in pelvic asymmetry in response to hindlimb lameness induction, withers movement asymmetry increased by 0.35–0.55 mm, but towards the contralateral side. In induced forelimb lameness, for each mm increase in head movement asymmetry, withers movement asymmetry increased by 0.05–0.10 mm, in agreement with the head movement asymmetry direction, both indicating lameness in the induced forelimb.Main limitationsResults must be confirmed in clinically lame horses trotting overground.ConclusionsThe vertical asymmetry pattern of the withers discriminated a head nod associated with true forelimb lameness from the compensatory head movement asymmetry caused by primary hindlimb lameness. Measuring movement symmetry of the withers may, thus, aid in determining primary lameness location.

SummaryBackgroundObjective lameness assessment is gaining more importance in a clinical setting, necessitating availability of reference values.ObjectivesTo investigate the between ‐path, ‐trial and ‐day variation, between and within horses, in the locomotion symmetry of horses in regular use that are perceived sound.Study designObservational study with replicated measurement sessions.MethodsTwelve owner‐sound horses were trotted on the straight line and on the lunge. Kinematic data were collected from these horses using 3D optical motion capture. Examinations were repeated on 12 occasions over the study which lasted 42 days in total. For each horse, measurements were grouped as five replicates on the first and second measurement days and two replicates on the third measurement day. Between measurement days 2 and 3, every horse had a break from examination of at least 28 days. Previously described symmetry parameters were calculated: RUD and RDD (Range Up/Down Difference; difference in upward/downward movement between right and left halves of a stride); MinDiff and MaxDiff (difference between the two minima/maxima of the movement); HHDswing and HHDstance (Hip Hike Difference‐swing/‐stance; difference between the upward movement of the tuber coxae during swingphase/stancephase). Data are described by the between‐measurement variation for each parameter. A linear mixed model was used to test for the effect of time, surface and path. Intraclass correlation coefficients (ICC) were calculated to access repeatability.ResultsMean between‐measurement variation was (MinDiff, MaxDiff, RUD, RDD): 13, 12, 20, 16 mm (head); 4, 3, 6, 4 mm (withers) and 5, 4, 6, 6 mm (pelvis); (HHDswing, HHDstance): 7 and 7 mm. More between‐measurement variation is seen on the first measurement day compared to the second and third measurement days. In general, less variation is seen with increasing number of repetitions. Less between‐measurement variation is seen on hard surface compared to soft surface. More between‐measurement variation is seen on the circle compared to the straight line. Between‐horse variation was clearly larger than within‐horse variation. ICC values for the head, withers and pelvis symmetry parameters were 0.68 (head), 0.76 (withers), 0.85 (pelvis).Main limitationsLunge measurements on a hard surface were not performed.ConclusionsBetween‐measurement variation may be substantial, especially in head motion. This should be considered when interpreting clinical data after repeated measurements, as in routine lameness assessments.

SummaryBackgroundInertial measurement unit (IMU) sensor‐based techniques are becoming more popular in horses as a tool for objective locomotor assessment.ObjectivesTo describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU sensors.Study designProspective validation study comparing IMU sensors and motion capture with force plate data.MethodsA total of seven Warmblood horses equipped with metacarpal/metatarsal IMU sensors and reflective markers for motion capture were hand walked and trotted over a force plate. Using four custom built algorithms hoof‐on/hoof‐off timing over the force plate were calculated for each trial from the IMU data. Accuracy of the computed parameters was calculated as the mean difference in milliseconds between the IMU or motion capture generated data and the data from the force plate, precision as the s.d. of these differences and percentage of error with accuracy of the calculated parameter as a percentage of the force plate stance duration.ResultsAccuracy, precision and percentage of error of the best performing IMU algorithm for stance duration at walk were 28.5, 31.6 ms and 3.7% for the forelimbs and −5.5, 20.1 ms and −0.8% for the hindlimbs, respectively. At trot the best performing algorithm achieved accuracy, precision and percentage of error of −27.6/8.8 ms/−8.4% for the forelimbs and 6.3/33.5 ms/9.1% for the hindlimbs.Main limitationsThe described algorithms have not been assessed on different surfaces.ConclusionsInertial measurement unit technology can be used to determine temporal kinematic stride variables at walk and trot justifying its use in gait and performance analysis. However, precision of the method may not be sufficient to detect all possible lameness‐related changes. These data seem promising enough to warrant further research to evaluate whether this approach will be useful for appraising the majority of clinically relevant gait changes encountered in practice.