Automatic detection of break-over phase onset in horses using hoof-mounted inertial measurement unit sensors

Abstract

A prolonged break-over phase might be an indication of a variety of musculoskeletal disorders and can be measured with optical motion capture (OMC) systems, inertial measurement units (IMUs) and force plates. The aim of this study was to present two algorithms for automatic detection of the break-over phase onset from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. The performance of these algorithms was evaluated by internal validation with an OMC system and a force plate separately. 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 over a force plate for internal validation while simultaneously the 3D position of three reflective markers, attached to lateral heel, lateral toe and lateral coronet of each hoof, were measured by six infrared cameras of an OMC system. The performance of the algorithms was evaluated by linear mixed model analysis. The acceleration algorithm was the most accurate with an accuracy between -9 and 23 ms and a precision around 24 ms (against OMC system), and an accuracy between -37 and 20 ms and a precision around 29 ms (against force plate), depending on gait and hoof. This algorithm seems promising for quantification of the break-over phase onset although the applicability for clinical purposes, such as lameness detection and evaluation of trimming and shoeing techniques, should be investigated more in-depth.

Fig 1

Generic illustration of the movement of the hoof (A), modified from Witte et al. [15], the signals of the acceleration (B), angular velocity (C), vertical force and first derivative of the vertical force (D), and vertical displacement of the heel and toe markers of the OMC system. The start of the break-over is depicted with the vertical dashed lines and the dots show the detected break-over from the different signals. The swing phase is underlined with a dark beam.

Fig 2. Distributions of time differences between both algorithms and reference methods for the break-over phase onset detection.

Time differences with the OMC system are depicted in the upper row and time differences with the force derivative are depicted in the bottom row. The different hoof/gait combinations are depicted with their own color.

Fig 3. Time differences and predicted values of time differences between force derivative and OMC system for break-over phase onset detection.

Time differences between the two reference methods are depicted in the upper figure with the different hoof/gait combinations depicted in their own color. In the bottom, the predicted values are indicated with dots for a certain hoof/gait combination and their 95% confidence intervals are shown by the whiskers. The dashed line indicates a predicted time difference of 0 ms.

Fig 4. Schematic representation of the predicted values of the time differences and their 95% confidence intervals.

The dots indicate the predicted value for a certain hoof/gait combination and the 95% confidence intervals are shown by the whiskers. The dashed line indicates a predicted time difference of 0 ms.