HoofStep horse animation. Create your digital horse so you can see where it is and what it does
The largest database in the world for horse behaviour
HoofStep monitors, registers, and measures every move and behaviour of a horse. The smart sensor in combination with Artificial Intelligence. 2016 was the year of proof of concept when our data analysis of registered horse behaviour identifies a broad spectrum of behaviour. It included all gaits, and also subtle changes such as a slight disturbance in e.g. the left front leg of a horse. That year we tested the different placements of the sensor. The placement on the forehead captures the richest amount of data through the movements of the head. This makes HoofStep unique since the chewing can be registered. The AI model and application register movements all the time it is on the horse. In the pasture, stalls as well as when riding.
The focus of the app
To make the data more accessible for the horse owner, the data is presented easily. The data is built on the location of the horse (GPS), physical movement, and activity in the shape of eating, resting, active, or highly active.
The alarm informs about changes in single behavior, eg. rolling, scraping, yawning, looking back, etc.
Interpretations of the app language
EAT
EAT - A dominant behaviour
When the horse eats independent of where, it eats standing, laying down or takes smaller steps (grazing)
REST
REST- All forms of resting
All types of rest, laying on the side or laying down, standing sleeping, and standing resting
ACTIVE
ACTIVE - Minor active behaviour
Walking and when the horse is not moving but performs an activity such as yawning, scratches, scraping the hoof, stretches, bites or licks
HIGHLY ACTIVE
HIGHLY ACTIVE- More active behaviour
Quicker movements such as trotting and canter. In this group of behaviour we have rolling, laying down and standing up again, headshaking and intense shaking as well as itching.
Applying HoofSteps data
HoofSteps monitoring and rich behavioural data are used in various research projects, eg, Equine monitoring in Brösarp/Kumlan where we for the 3rd year in a row, monitor yearlings. We analyse the data in-depth, to support the theory and old knowledge that this type of pasture management early on increases the longevity and sustainability of promising showjumpers. Another project in Austria where behaviour of geriatric horses is being analysed.