Artificial intelligence algorithms to predict risk of injury in racehorses.

预测赛马受伤风险的人工智能算法。

• 批准号: LP210200798
• 负责人: Prof Simon Bailey
• 金额: $ 23.15万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-02-08 至 2026-02-07
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP210200798
• 关键词: Artificial; intelligence; algorithms; predict; risk

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.

该项目将解决预测和预防由于过度（或不足）训练导致的赛马灾难性和职业限制肢体损伤和心律失常的迫切需要。利用集成在鞍布上的GPS和运动传感器的数据，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为风险矩阵。记录的心率和心电图数据也将使用人工智能进行分析，以检测心律失常发展的早期证据。该系统将改善赛马的福利，提供一个简单的界面，当受伤的风险变得很高时，警告训练员，以防止灾难性的故障。