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.
Highlights
Preprocessed data of one measurement in trot can be seen in S1 Fig. The time differences between the detection of the break-over phase onset of both algorithms and the two reference methods (OMC and force plate) were normally distributed
The distribution of the angular velocity algorithm versus optical motion capture (OMC) system (Fig 2B) shows a smaller half bell shape curve, ranging from -100 to 10 ms, and a mean of -32.77 ms with lower values found for right front (RF) in trot
The distribution of the acceleration algorithm versus force derivative (Fig 2C) shows a bell shape curve ranging from -155 to 125 ms and a mean of -12.18 ms with lower values found for right hind (RH) in walk and higher values found for RF in walk
Summary
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 aim of this study was to present two algorithms for automatic detection of the break-over phase onset from the acceleration and angular velocity data measured by hoof-mounted IMUs in walk and trot on a hard surface
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