Kinematic discrimination of ataxia in horses is facilitated by blindfolding

BACKGROUND: Agreement among experienced clinicians is poor when assessing the presence and severity of ataxia, especially when signs are mild. Consequently, objective gait measurements might be beneficial for assessment of horses with neurological diseases. OBJECTIVES: To assess diagnostic criteria using motion capture to measure variability in spatial gait-characteristics and swing duration derived from ataxic and non-ataxic horses, and to assess if variability increases with blindfolding. STUDY DESIGN: Cross-sectional. METHODS: A total of 21 horses underwent measurements in a gait laboratory and live neurological grading by multiple raters. In the gait laboratory, the horses were made to walk across a runway surrounded by a 12-camera motion capture system with a sample frequency of 240 Hz. They were made to walk normally and with a blindfold in at least three trials each. Displacements of reflective markers on head, fetlock, hoof, fourth lumbar vertebra, tuber coxae and sacrum derived from three to four consecutive strides were processed and descriptive statistics, receiver operator characteristics (ROC) to determine the diagnostic sensitivity, specificity and area under the curve (AUC), and correlation between median ataxia grade and gait parameters were determined. RESULTS: For horses with a median ataxia grade ≥2, coefficient of variation for the location of maximum vertical displacement of pelvic and thoracic distal limbs generated good diagnostic yield. The hoofs of the thoracic limbs yielded an AUC of 0.81 with 64% sensitivity and 90% specificity. Blindfolding exacerbated the variation for ataxic horses compared to non-ataxic horses with the hoof marker having an AUC of 0.89 with 82% sensitivity and 90% specificity. MAIN LIMITATIONS: The low number of consecutive strides per horse obtained with motion capture could decrease diagnostic utility. CONCLUSIONS: Motion capture can objectively aid the assessment of horses with ataxia. Furthermore, blindfolding increases variation in distal pelvic limb kinematics making it a useful clinical tool

Validation of distal limb mounted inertial measurement unit sensors for stride detection in Warmblood horses at walk and trot

Background: Inertial measurement unit (IMU) sensor-based techniques are becoming more popular in horses as a tool for objective locomotor assessment. Objectives: To describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU sensors. Study design: Prospective validation study comparing IMU sensors and motion capture with force plate data. Methods: A 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. Results: Accuracy, 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 limitations: The described algorithms have not been assessed on different surfaces. Conclusions: Inertial 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

Is a standalone inertial measurement unit accurate and precise enough for quantification of movement symmetry in the horse?

Standalone ‘low-cost’ inertial measurement units (IMUs) could facilitate large-scale studies into establishing minimal important differences (MID) for orthopaedic deficits (lameness) in horses. We investigated accuracy and limits of agreement (LoA) after correction of magnitude-dependent differences of a standalone 6 degree-of-freedom IMU compared with an established IMU-based gait analysis system (MTx) in six horses for two anatomical landmarks (sacrum and sternum). Established symmetry measures were calculated from vertical displacement: symmetry index (SI), difference between minima (MinDiff) and difference between maxima (MaxDiff). For the sacrum, LoA were ± 0.095 for SI, ± 6.6 mm for MinDiff and ± 4.3 mm for MaxDiff. For the sternum, LoA values were ± 0.088 for SI, ± 5.0 mm for MinDiff and ± 4.2 mm for MaxDiff. Compared with reference data from mildly lame horses, SI values indicate sufficient precision, whereas MinDiff and MaxDiff values are less favourable. Future studies should investigate specific calibration and processing algorithms further improving standalone IMU performance

GaitKeeper: a system for measuring canine gait

It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs’ gaits are frequently assessed in a veterinary setting to detect signs of lameness. Despite this, a reliable, affordable and objective method to assess lameness in dogs is lacking. Most described canine lameness assessments are subjective, unvalidated and at high risk of bias. This means reliable, early detection of canine gait abnormalities is challenging, which may have detrimental implications for dogs’ welfare. In this paper, we draw from approaches and technologies used in human movement science and describe a system for objectively measuring temporal gait characteristics in dogs (step-time, swing-time, stance-time). Asymmetries and variabilities in these characteristics are of known clinical significance when assessing lameness but presently may only be assessed on coarse scales or under highly instrumented environments. The system consists an inertial measurement unit, containing a 3-axis accelerometer and gyroscope coupled with a standardized walking course. The measurement unit is attached to each leg of the dog under assessment before it is walked around the course. The data by the measurement unit is then processed to identify steps and subsequently, micro-gait characteristics. This method has been tested on a cohort of 19 healthy dogs of various breeds ranging in height from 34.2 cm to 84.9 cm. We report the system as capable of making precise step delineations with detections of initial and final contact times of foot-to-floor to a mean precision of 0.011 s and 0.048 s, respectively. Results are based on analysis of 12,678 foot falls and we report a sensitivity, positive predictive value and F-score of 0.81, 0.83 and 0.82 respectively. To investigate the effect of gait on system performance, the approach was tested in both walking and trotting with no significant performance deviation with 7249 steps reported for a walking gait and 4977 for a trotting gait. The number of steps reported for each leg were approximately equal and this consistency was true in both walking and trotting gaits. In the walking gait 1965, 1790, 1726 and 1768 steps were reported for the front left, front right, hind left and hind right legs respectively. 1361, 1250, 1176 and 1190 steps were reported for each of the four legs in the trotting gait. The proposed system is a pragmatic and precise solution for obtaining objective measurements of canine gait. With further development, it promises potential for a wide range of applications in both research and clinical practice

Automatic hoof-on and -off detection in horses using hoof-mounted inertial measurement unit sensors

For gait classification, hoof-on and hoof-off events are fundamental locomotion characteristics of interest. These events can be measured with inertial measurement units (IMUs) which measure the acceleration and angular velocity in three directions. The aim of this study was to present two algorithms for automatic detection of hoof-events from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. Seven Warmblood horses were equipped with two wireless IMUs, which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted on a lead over a force plate for internal validation. The agreement between the algorithms for the acceleration and angular velocity signals with the force plate was evaluated by Bland Altman analysis and linear mixed model analysis. These analyses were performed for both hoof-on and hoof-off detection and for both algorithms separately. For the hoof-on detection, the angular velocity algorithm was the most accurate with an accuracy between 2.39 and 12.22 ms and a precision of around 13.80 ms, depending on gait and hoof. For hoof-off detection, the acceleration algorithm was the most accurate with an accuracy of 3.20 ms and precision of 6.39 ms, independent of gait and hoof. These algorithms look highly promising for gait classification purposes although the applicability of these algorithms should be investigated under different circumstances, such as different surfaces and different hoof trimming conditions

An investigation into the efficacy of kinematics and kinetics method for stride-characteristic measurements of horses trotting on a treadmill

The aim of this study was to investigate the validity of stride characteristic measurements taken from the sternum by means of an Optical Motion Capture System (OMCS) and an Inertia Measurement Unit (IMU), in comparison with OMCS hoof markers. Measurements were taken from sound horses of a range of breeds, trotting at self-selected speeds on a treadmill (OMCS N=15; IMU N=4). Hoof marker trajectories were compared in terms of dorsoventral position (pZ), craniocaudal velocity (vX) and dorsoventral velocity (vZ). Contra-laterally coupled limbs were compared at beginning and end of stance according to vX. A Girth Marker (GM) placed over the sternum was used to identify beginning and end of stance of each diagonal using dorsoventral acceleration (aZ) and dorsoventral velocity (vZ) respectively. These were compared with hoof marker vX. GM aZ and vZ were then validated against the same measurements taken by an IMU measuring at the same time from the same location. No significant difference (p < 0.05) was found by ANOVA between hoof marker trajectories pZ, vX or vZ at beginning or end of stance. No significant difference was found by t-test or ICC between contralaterally coupled limbs at beginning or end of stance. GM aZ and vZ could be used to identify beginning and end of stance for each diagonal without significant difference from hoof vX timings according to t-test and ICC. OMCS GM and IMU did not differ in terms of velocity (peak or trough timing or amplitude, or absolute difference: peak minus trough), or acceleration peak timing, trough timing or trough amplitude according to t-test or ICC. However, OMCS GM and IMU differed significantly in terms of acceleration peak amplitude (p = .01, ICC = 0.46) and absolute difference (p = .04, ICC = 0.66). The sternum can be used as a site to collect data providing accurate information on beginning or end of stance of horses with no advanced placement of contralaterally coupled limbs, whilst trotting at self selected speeds on a treadmill. Temporal acceleration data, and temporal or amplitudal velocity data are sufficient to identify beginning and end of stance from the sternum using an IMU. Amplitudal acceleration data from an IMU should be further investigated before assumed valid under these conditions

Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning

For centuries humans have been fascinated by the natural beauty of horses in motion and their different gaits. Gait classification (GC) is commonly performed through visual assessment and reliable, automated methods for real-time objective GC in horses are warranted. In this study, we used a full body network of wireless, high sampling-rate sensors combined with machine learning to fully automatically classify gait. Using data from 120 horses of four different domestic breeds, equipped with seven motion sensors, we included 7576 strides from eight different gaits. GC was trained using several machine-learning approaches, both from feature-extracted data and from raw sensor data. Our best GC model achieved 97% accuracy. Our technique facilitated accurate, GC that enables in-depth biomechanical studies and allows for highly accurate phenotyping of gait for genetic research and breeding. Our approach lends itself for potential use in other quadrupedal species without the need for developing gait/animal specific algorithms

A simple method for equine kinematic gait event detection

Background Previous studies have validated methods for determining kinematic gait events using threshold-based methods, however a simple method is yet to be identified that can be successfully applied to walk, trot and canter. Objectives To develop a simple kinematic method to identify the timing of hoof-on, peak vertical force and hoof-off, which can be applied to walk, trot and canter. Study design In-vivo method authentication study. Methods The horses (n = 3) were ridden in walk, trot and canter down a runway with four force plates arranged linearly. Three-dimensional forces were recorded at a sampling rate of 960 Hz and were synchronised with a ten-camera motion analysis system sampling at 120 Hz. Events identified from the vertical ground reaction force (GRFz) data were hoof-on (GRFz>50N), peak vertical force (GRFzpeak) and hoof-off (GRFz<50N). Kinematic identification of hoof-on and hoof-off events was based on sagittal planar angles of the fore and hindlimbs. Peak metacarpophalangeal/metatarsophalangeal (MCP/MTP) joint extension was used to assess the time of GRFzpeak. The accuracy (mean) and precision (s.d.) of the time difference between the kinetic and kinematic events were calculated for the fore and hindlimbs at each gait. Results Hoof-off was determined with better accuracy (range: -3.94 to 8.33 ms) and precision (5.43 to 11.39 ms) than hoof-on across all gaits. Peak MCP angle (5.83 to 19.65 ms) was a more precise representation of GRFzpeak than peak MTP angle (11.49 to 67.75 ms). Main limitations The sample size was small and, therefore, further validation is required. The proposed method was tested on one surface. Conclusions A simple kinematic method of detecting hoof-on, hoof-off and GRFzpeak is here proposed for walk, trot and canter. Further work should focus on validating the methodology in a larger number of horses and extending the method for use on surfaces with varying compliance