Every horse has its own natural movement characteristics, such as stride duration, speed and stride length. Traditionally, scientists had been able to evaluate the movement of horses visually. But the human eye is only capable of registering images with a frequency of 20 Hz. This makes the human capacity for assessment insufficient in order to arrive at a consistent and objective evaluation of the functioning of the horse’s locomotor system, especially when diagnosing lameness – much less when predicting a horse’s performance.

A recent innovation for the measurement of these characteristics in different horses is the high cost 3D motion camera equipment. This can produce accurate data but it requires a lengthy, laborious set-up in a very controlled environment. The obtained information is only from the side and the few strides that are in view of the camera.

In the EquiMoves project we developed a system that uses Inertia’s sensor nodes as mobile measuring units attached to the legs of the horse, the withers and the head. The movement coordination, temporal and spatial gait parameters are extracted from the signals retrieved in all gaits of the horse. The analysis quantifies scientifically the differences between horses but also response on training, shoeing, nerve blocking, medication, etc.

Horse wearing the wireless gait analysis system

Data Collection and Analysis

The EquiMoves system collects data from horses instrumented with ProMove-mini sensor nodes on the legs, the withers and the head. Each node is attached using a custom made holster.


Attachment modalities of ProMove-mini sensor nodes to the horse

The sensors are set to a sampling rate of 200Hz, with the low g accelerometer set at ± 16g and the high-g accelerometer set at ± 200g. The data is wirelessly transmitted to the Inertia Gateway and also stored using the internal memory of each sensor. Synchronization among all sensors is less than 100ns.

The accurate and precise detection of the stride parameters is a crucial prerequisite for the proper determination of temporal and spatial stride characteristics. Using various custom-built algorithms, we determine the relevant 3D motion parameters for assisting the researchers and veterinary practitioners in early detection of lameness in horses.

The figures below show an example of the stride angle tracks during the sagittal and coronal movements of each horse leg and during the cyclic vertical movements of the withers, synchronized with the hoof-on and hoof-off events.

Hoof-on and hoof-off events for each horse leg

Hoof-on and hoof-off events correlated with the movement of the withers