Artificial intelligence algorithms to predict risk of injury in racehorses.

该项目将解决预测和预防因训练过多(或训练不足)而导致的赛马四肢损伤和心律失常的灾难性和职业限制的迫切需要。使用来自GPS的数据和集成到鞍布中的运动传感器，人工智能算法将在训练期间将速度、步态和步幅特征的累积数据以及受伤数据转换到风险矩阵中。记录的心率和心电数据也将使用人工智能进行分析，以发现心律失常发生的早期证据。该系统将改善赛马的福利，提供一个简单的界面，当受伤风险变得很高时向训练员发出警告，以防止灾难性的故障。

This project will address the urgent need for predicting and preventing catastrophic and career limiting limb injuries and cardiac arrhythmias in racehorses due to over (or under) training. Using data from GPS and movement sensors integrated into saddlecloths, artificial intelligence algorithms will convert cumulative data on speed, gait, and stride characteristics during training, along with injury data, into a risk matrix. Recorded heart rate and ECG data will also be analysed using artificial intelligence to detect early evidence of the development of cardiac arrhythmias. The system will improve racehorse welfare, providing a simple interface to warn trainers when risk of injury becomes high, in order to prevent catastrophic breakdown.