Non-Invasive Lactate Estimation Using Wearable Sensors for Remote Fatigue Assessment in Horses

Abstract

Exercise-induced fatigue is a complex phenomenon that can significantly impact the health and welfare of horses. Traditional methods for assessing fatigue in horses, such as plasma lactate accumulation (LA) measurement, can be invasive and require the presence of a veterinarian on-site. In this paper, we propose the use of body-mounted inertial measurement units (IMUs) and a heart rate (HR) monitor as a non-invasive and veterinarian independent approach for assessing fatigue by estimating LA in horses during exercise. LA estimation models were trained using signal-based features and kinematic parameters extracted from IMUs. As an outcome, the accuracy of the best performing model based on two IMUs and HR was 0.11 mmol/L and 4.89% (root mean square error and mean absolute percentage error). This approach demonstrates the potential for remote health monitoring in animals, which can be particularly valuable for those in remote locations or with limited access to specialized veterinary care.