Validation of inertial measurement units to detect and predict horse behaviour while stabled

Abstract

BackgroundMusculoskeletal injuries are observed in Thoroughbred racehorses and may become catastrophic. Currently, there are limited methods for early detection of such injuries. Most injuries develop gradually due to accumulated damage, providing the opportunity for early detection. Horses experiencing pain or lameness may exhibit changes in behaviour so the development of an objective, real‐time system monitoring horse behaviour may enable detection of bone injuries before catastrophic failure.ObjectivesTo determine whether intensive observational methods of assessing horse behaviour can be replaced by use of inertial measurement units (IMUs).Study designValidation study assessing IMU use against video observation.MethodsSix hospitalised Thoroughbreds (algorithm training data) and 19 Thoroughbred racehorses in‐training (algorithm testing data) were equipped with an IMU placed on the lateral side of both forelimbs (left fore, LF; right fore, RF) and monitored in a stable for 4 h. An algorithm was developed to classify behaviour and then validated against video recordings.ResultsStanding was the most prevalent behaviour (LF 88.8%, 95% confidence interval [CI] 88.7–89.0; RF 88.5%, 95% CI 88.4–88.7). IMU classification of recumbent and standing activities showed excellent agreement (sensitivity) with video observation (>98%). This was followed by stepping (LF 89.4%, RF 85.5%) then weight‐shifting (LF 54.3%, RF 61.5%). Predictions from the algorithm showed misclassification of 2.5% (LF 5500/225 352, RF 5218/210 170). Excluding standing, misclassification was 6.8% (1705/25 158) and 7.5% (1812/24 077) for the left and right forelimbs, respectively, with pawing and weight‐shifting most frequently misclassified.Main limitationsIncreasing the number of horses and types of behaviours observed may improve predictions.ConclusionsIMUs displayed a high sensitivity to movement on a small number of horses, and with further validation they have the potential to effectively monitor behaviour of racehorses in training. However, more sensitive methods may be needed to validate the classification of weight‐shifting behaviour. Future studies should evaluate the association between each behaviour and musculoskeletal injury.