Detection of hoof-on and -off events are essential to gait classification in horses. Wearable sensors have been endorsed as a convenient alternative to the traditional force plate-based method. The aim of this study was to propose and validate inertial sensor-based methods of gait event detection, reviewing different sensor locations and their performance on different gaits and exercise surfaces. Eleven horses of various breeds and ages were recruited to wear inertial sensors attached to the hooves, pasterns and cannons. Gait events detected by pastern and cannon methods were compared to the reference, hoof-detected events. Walk and trot strides were recorded on asphalt, grass and sand. Pastern-based methods were found to be the most accurate and precise for detecting gait events, incurring mean errors of between 1 and 6ms, depending on the limb and gait, on asphalt. These methods incurred consistent errors when used to measure stance durations on all surfaces, with mean errors of 0.1 to 1.16% of a stride cycle. In conclusion, the methods developed and validated here will enable future studies to reliably detect equine gait events using inertial sensors, under a wide variety of field conditions.

中文翻译：

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在沥青、沙地和草地上行走和小跑时，使用可穿戴惯性传感器自动检测马匹的开蹄和脱蹄。


检测蹄起落事件对于马的步态分类至关重要。可穿戴传感器已被认可为传统测力台方法的便捷替代方案。本研究的目的是提出并验证基于惯性传感器的步态事件检测方法，审查不同的传感器位置及其在不同步态和运动表面上的性能。招募了十一匹不同品种和年龄的马，在马蹄、脚腕和大炮上安装惯性传感器。将通过脚掌和大炮方法检测到的步态事件与参考的蹄检测事件进行比较。记录了在沥青、草地和沙子上行走和小跑的步幅。人们发现，基于 Pastern 的方法是检测步态事件最准确和精确的方法，在沥青上，根据肢体和步态，平均误差在 1 到 6 毫秒之间。当用于测量所有表面上的站立持续时间时，这些方法会产生一致的误差，平均误差为步幅周期的 0.1% 至 1.16%。总之，这里开发和验证的方法将使未来的研究能够在各种现场条件下使用惯性传感器可靠地检测马的步态事件。