Visual gait assessment by equine veterinarians is an important part of the diagnosis of equine locomotor disorders, and the measurement of locomotor asymmetry can provide objective support for the diagnosis. In order to investigate and analyze equine asymmetry index thresholds as a way to distinguish healthy horses from lame ones, Claire Macaire's scientific team from France developed the EQUISYM® system, which consists of seven IMUs (inertial measurement units) placed on the horse's head, shoulder, pelvis and four cannon bones, capable of recording the horse's movement data in real time, experimentally using a customized Matlab 2020a script was used to process the data to obtain the mean and standard deviation (SD) of the asymmetry index (AI), and the data were evaluated for normality using a graphical method using the software RStudio.

The veterinarians first performed a motor assessment, based on which the horses were divided into five groups: 67 horses with right forelimb (RF) lameness, 62 horses with left forelimb (LF) lameness, 23 horses with right hindlimb (RH) lameness, 23 horses with left hindlimb (LH) lameness, and 29 able-bodied horses.

Horses were tested at two trots on a hard straight track and IMU data on four cannon bones determined the time of the stance phase, a stride was defined as the time between two consecutive pedal steps of the left forelimb. Vertical displacements of the head, shoulders and pelvis were split into stride lengths. Acceleration signals measured along the dorsoventral axis of the horse were integrated twice and then high-pass filtered using a fourth-order Butterworth filter with a cutoff frequency set at 1 Hz to obtain displacement profiles.

Four variables were calculated for each IMU position based on the vertical displacement of the head, shoulders and pelvis occurring within a stride, the following asymmetry index (AI), expressed as a percentage of the maximum range of motion within a stride.

AI-Minis the difference between the left and right of the lowest point of vertical motion.

AT-Maxis the difference between the left and right of the highest point of vertical motion.

AI-upis the difference between the left and right of the upward range of motion during the propulsion phase.

AI-downis the difference between the left and right of the downward range of motion of the damping stage. ,

A positive AI value indicates that the amplitude of motion is smaller when the right foot is standing than when the left foot is standing, and a negative AI value indicates the opposite.

After analyzing the asymmetry index with the software RStudio, the receiver operating characteristic curve was plotted and the threshold value with the highest specificity and sensitivity was calculated. In this experiment, if the sum of sensitivity and specificity is higher than 150%, the index is considered to have good discrimination ability.

Only AI with left and right lamenesses whose sum of sensitivity and specificity exceeded 150% were plotted. Three ranges of values are indicated: yellow indicates the 95% confidence interval around the threshold (95% CI), green indicates values below the 95% CI (sound horses), and red indicates values above the 95% CI (lame horses).

The images show thresholds of sensitivity and specificity exceeding 150% for the identification of right and left lameness and their confidence intervals (CI) of 95%, confirming that vertical displacement of the horse's head and shoulders is an important indicator of forelimb lameness, while vertical displacement of the pelvis distinguishes hindlimb lameness.

In this experiment, the EQUISYM® system, consisting of 7 IMUs, provided strong support for the experiment and can provide technical support for clinical diagnosis by veterinarians to a certain extent, but further research is needed in the future to investigate the interrelationship between head, shoulder and pelvic movements in horses and provide more information about the relationship between lameness recognition and indices in various clinical situations to achieve a more accurate and comprehensive identification of lameness conditions in horses.