As a first step in achieving an evidence-based classification system for the sport of Para Dressage, there is a clear need to define elite dressage performance. Previous studies have attempted to quantify performance with able-bodied riders using scientific methods; however, definitive measures have yet to be established for the horse and/or the rider. This may be, in part, due to the variety of movements and gaits that are found within a dressage test and also due to the complexity of the horse-rider partnership. The aim of this review is therefore to identify objective measurements of horse performance in dressage and the functional abilities of the rider that may influence them to achieve higher scores. Five databases (SportDiscuss, CINAHL, MEDLINE, EMBASE, VetMed) were systematically searched from 1980 to May 2018. Studies were included if they fulfilled the following criteria: (1) English language; (2) employ objective, quantitative outcome measures for describing equine and human performance in dressage; (3) describe objective measures of superior horse performance using between-subject comparisons and/or relating outcome measures to competitive scoring methods; (4) describe demands of dressage using objective physiological and/or biomechanical measures from human athletes and/or how these demands are translated into superior performance. In total, 773 articles were identified. Title and abstract screening resulted in 155 articles that met the eligibility criteria, 97 were excluded during the full screening of articles, leaving 58 included articles (14 horse, 44 rider) involving 311 equine and 584 able-bodied human participants. Mean ± sd (%) quality scores were 63.5 ± 15.3 and 72.7 ± 14.7 for the equine and human articles respectively. Significant objective measures of horse performance (n = 12 articles) were grouped into themes and separated by gait/movement. A range of temporal variables that indicated superior performance were found in all gaits/movements. For the rider, n = 5 articles reported variables that identified significant differences in skill level, which included the postural position and ROM of the rider’s pelvis, trunk, knee and head. The timing of rider pelvic and trunk motion in relation to the movement of the horse emerged as an important indicator of rider influence. As temporal variables in the horse are consistently linked to superior performance it could be surmised that better overall dressage performance requires minimal disruption from the rider whilst the horse maintains a specific gait/movement. Achieving the gait/movement in the first place depends upon the intrinsic characteristics of the horse, the level of training achieved and the ability of the rider to apply the correct aid. The information from this model will be used to develop an empirical study to test the relative strength of association between impairment and performance in able-bodied and Para Dressage riders.

Low-frequency noise attenuation and normalisation are fundamental signal processing (SP) methods for surface electromyography (sEMG), but are absent, or not consistently applied, in equine biomechanics. The purpose of this study was to examine the effect of different band-pass filtering and normalisation conventions on sensitivity for identifying differences in sEMG amplitude-related measures, calculated from leading (LdH) and trailing hindlimb (TrH) during canter, where between-limb differences in vertical loading are known. sEMG and 3D-kinematic data were collected from the right Biceps Femoris in 10 horses during both canter leads. Peak hip and stifle joint angle and angular velocity were calculated during stance to verify between-limb biomechanical differences. Four SP methods, with and without normalisation and high-pass filtering, were applied to raw sEMG data. Methods 1 (M1) to 4 (M4) included DC-offset removal and full-wave rectification. Method 2 (M2) included additional normalisation relative to maximum sEMG across all strides. Method 3 (M3) included additional high-pass filtering (Butterworth 4th order, 40 Hz cut-off), for artefact attenuation. M4 included the addition of high-pass filtering and normalisation. Integrated EMG (iEMG) and average rectified value (ARV) were calculated using processed sEMG data from M1 – M4, with stride duration as the temporal domain. sEMG parameters, within M1 – M4, and kinematic parameters were grouped by LdH and TrH and compared using repeated measures ANOVA. Significant between-limb differences for hip and stifle joint kinematics were found, indicating functional differences in hindlimb movement. M2 and M4, revealed significantly greater iEMG and ARV for LdH than TrH (P<0.01), with M4 producing the lowest P-values and largest effect sizes. Significant between-limb differences in sEMG parameters were not observed with M1 and M3. The results indicate that equine sEMG SP should include normalisation and high-pass filtering to improve sensitivity for identifying differences in muscle function associated with biomechanical changes during equine gait.

Selection and training practices for jumping horses have not yet been validated using objective performance analyses. This study aimed to quantify the differences and relationships between movement and muscle activation strategies in horses with varying jump technique to identify objective jumping performance indicators. Surface electromyography (sEMG) and three-dimensional kinematic data were collected from horses executing a submaximal jump. Kinematic variables were calculated based on equestrian-derived performance indicators relating to impulsion, engagement and joint articulation. Horses were grouped using an objective performance indicator—center of mass (CM) elevation during jump suspension (ZCM). Between-group differences in kinematic variables and muscle activation timings, calculated from sEMG data, were analyzed using one-way ANOVA. Statistical parametric mapping (SPM) evaluated between-group differences in time and amplitude-normalized sEMG waveforms. Relationships between movement and muscle activation were evaluated using Pearson correlation coefficients. Horses with the greatest ZCM displayed significantly (p < 0.05) shorter gluteal contractions at take-off, which were significantly correlated (p < 0.05) with a faster approach and more rapid hindlimb shortening and CM vertical displacement and velocity, as well as shorter hindlimb stance duration at take-off. Findings provide objective support for prioritizing equestrian-derived performance indicators related to the generation of engagement, impulsion and hindlimb muscle power when selecting or training jumping horses.

High-pass filtering (HPF) is a fundamental signal processing method for the attenuation of low-frequency noise contamination, namely baseline noise and movement artefact noise, in human surface electromyography (sEMG) research. Despite this, HPF is largely overlooked in equine sEMG research, with many studies not applying, or failing to describe, the application of HPF. An optimal HPF cut-off frequency maximally attenuates noise while minimally affecting sEMG signal power, but this has not been investigated for equine sEMG signals. The aim of this study was to determine the optimal cut-off frequency for attenuation of low-frequency noise in sEMG signals from the Triceps Brachii and Biceps Femoris of 20 horses during trot and canter. sEMG signals were HPF with cut-off frequencies ranging from 0 to 80 Hz and were subjected to power spectral analysis and enveloped using RMS to calculate spectral peaks, indicative of motion artefact, and signal loss, respectively. Processed signals consistently revealed a low-frequency peak between 0 and 20 Hz, which was associated with motion artefact. Across all muscles and gaits, a 30-40 Hz cut-off fully attenuated the low-frequency peak with the least amount of signal loss and was therefore considered optimal for attenuating low-frequency noise from the sEMG signals explored in this study.

The relationship between lameness-related adaptations in equine appendicular motion and muscle activation is poorly understood and has not been studied objectively. The aim of this study was to compare muscle activity of selected fore- and hindlimb muscles, and movement of the joints they act on, between baseline and induced forelimb (iFL) and hindlimb (iHL) lameness. Three-dimensional kinematic data and surface electromyography (sEMG) data from the fore- (triceps brachii, latissimus dorsi) and hindlimbs (superficial gluteal, biceps femoris, semitendinosus) were bilaterally and synchronously collected from clinically non-lame horses (n = 8) trotting over-ground (baseline). Data collections were repeated during iFL and iHL conditions (2–3/5 AAEP), induced on separate days using a modified horseshoe. Motion asymmetry parameters and continuous joint and pro-retraction angles for each limb were calculated from kinematic data. Normalized average rectified value (ARV) and muscle activation onset, offset and activity duration were calculated from sEMG signals. Mixed model analysis and statistical parametric mapping, respectively, compared discrete and continuous variables between conditions (α= 0.05). Asymmetry parameters reflected the degree of iFL and iHL. Increased ARV occurred across muscles following iFL and iHL, except non-lame side forelimb muscles that significantly decreased following iFL. Significant, limb-specific changes in sEMG ARV, and activation timings reflected changes in joint angles and phasic shifts of the limb movement cycle following iFL and iHL. Muscular adaptations during iFL and iHL are detectable using sEMG and primarily involve increased bilateral activity and phasic activation shifts that reflect known compensatory movement patterns for reducing weightbearing on the lame limb. With further research and development, sEMG may provide a valuable diagnostic aid for quantifying the underlying neuromuscular adaptations to equine lameness, which are undetectable through human observation alone.