Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

SLEIP AI -Computer Vision assessment of lameness in horses

Reference number
Coordinator Sleip AI AB
Funding from Vinnova SEK 900 000
Project duration June 2021 - June 2022
Status Completed
Venture Innovative Startups
Call Innovative Startups step 2 spring 2021

Important results from the project

The project goal was to expand the technical capacity of our veterinary SaaS product by developing movement analysis of horses during lungeing. Our previous product was able to analyze horses in straight line trot. To provide a more complete diagnostic tool to our customers, we wanted to explore the possibility of performing this analysis also on the circle, a complex challenge for Computer Vision technology. After successful technical development and validation, we have created a fully integrated product function that has received very positive responses from our customers.

Expected long term effects

The project results have taken the company a big step forward through a markedly improved sales offer to our customers where we can provide a complete solution for analysis of lameness in horses via a smartphone. The new product function has shortly after launch become very popular with our initial test group. Today, all our costomers use it and it generates more recordings than the original "straight line product function".

Approach and implementation

Collection of training and reference data went according to plan. After building the database, algorithms and neural networks were developed to be able to create a robust analysis of movement asymmetry during lungeing. This very technically challenging part of the project resulted in high quality results that underwent validation and continuous benchmarking during the project. Development of new signal processing algorithms gave new insights to how we can improve the product. User interfaces were developed iteratively via user feedback.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 29 July 2022

Reference number 2021-01556