The spectacle of a galloping horse suddenly falling to the ground after suffering a catastrophic musculoskeletal injury is calamitous to witness. Such injuries have been a tragic part of many high-speed equine competitive events since time immemorial, and identifying horses at greatest risk of incurring such injuries has been a clinical conundrum that has resisted resolution for just as long. However, recent advancements in accelerometer-based sensor technology are providing unprecedented insights into the forces experienced by racehorses during high-speed locomotion, potentially enabling early detection of at-risk horses before a catastrophic event occurs.
Identifying Horses at Risk
Musculoskeletal injuries are responsible for a high rate of racehorse attrition, with even the best outcomes resulting in loss of income, lower field numbers, and fewer career starts. In the worst circumstances, these injuries lead to loss of use or life for the horse and life-altering or -ending injuries to the jockeys. Catastrophic injuries are often the result of an ongoing acute or chronic disease process, with consistent lesion characteristics and locations specific to individual bones.
The dilemma is that these preexisting pathologies and disease processes often do not seem clinically apparent, leaving horses deemed sound and fit to race by trainers and veterinarians alike. Until recently, there has been a lag within Thoroughbred racing in the application of available technologies to screen for these at-risk horses.
Accelerometer-Based Sensor Systems
Advances in human athlete monitoring have paved the way for similar technologies to be applied to equine athletes. Accelerometer-based inertial measurement unit (IMU) sensors are now being used to continuously record the locomotory movements of racehorses at high frequencies. These sensors, worn in the saddle cloth behind the saddle, identify horses at greatest risk of suffering a musculoskeletal injury if they continue to train and race.
The IMU sensors measure accelerations and decelerations in three planes of motion – dorsoventral, longitudinal, and mediolateral – at a sampling rate of 800 Hz, for a combined total of 2,400 force measurements per second. This high-frequency data allows the system to capture the forces and vibrations experienced by a horse’s body during the high-speed gallop, which differ significantly from the forces encountered during slower gaits like the trot.
Stride Pattern Analysis
The sensor data is analyzed by an algorithm that compares an individual horse’s stride pattern to an established “ideal” pattern drawn from the stride files of 37 graded stakes-winning horses. Horses are assigned a risk factor from 1 to 5, with 5 indicating the highest risk of a catastrophic injury.
Horses with a risk factor of 5 demonstrate a stride pattern that is over 5 standard deviations from the ideal, and are 950 times more likely to suffer a fatal or career-ending injury than those in the lowest risk category. The algorithm identifies abnormalities in the horse’s motion, such as increased mediolateral acceleration or uneven loading of the limbs, that may indicate underlying pathology.
Case Studies in Early Detection
The use of these accelerometer-based sensors has enabled the early detection of potentially catastrophic injuries in several racehorses. In a series of three cases reported in the Journal of the American Veterinary Medical Association, horses identified as being at very high risk (risk factor 5) underwent advanced imaging within 10 days.
In the first two cases, 18F-sodium fluoride positron emission tomography (PET) scans revealed increased uptake in the condyles of the third metacarpal bone, indicating potential increased risk of condylar fracture. In the third case, the PET scan showed remodeling of the third carpal bone, with an impending slab fracture subsequently identified on radiographs.
Following periods of convalescence, the first two horses were able to return to racing, with the sensor system no longer identifying them as being at high risk. The third horse returned to training but had not yet returned to racing at the time of reporting.
Implications for Racehorse Welfare
The ability of these accelerometer-based sensor systems to identify horses at high risk of catastrophic injury before a terminal event occurs is a significant advancement for the Thoroughbred racing industry. By providing objective, data-driven insights into a horse’s biomechanics during high-speed exercise, these sensors offer veterinarians and trainers the opportunity to intervene and potentially prevent severe, life-altering injuries.
Historically, the majority of catastrophic musculoskeletal injuries have been associated with preexisting pathologies that were not clinically apparent. The traditional approach of visual assessment at the trot often fails to detect the subtle abnormalities that manifest during the high-intensity gallop. The high-frequency, multi-dimensional data provided by the IMU sensors allows for the identification of these subclinical issues, which can then be further evaluated through advanced imaging techniques.
The implementation of this sensor technology represents a significant step forward in improving racehorse welfare and reducing the incidence of catastrophic injuries. By empowering veterinarians and trainers with objective data to identify at-risk horses, the racing industry can take proactive measures to protect the safety and wellbeing of both equine and human athletes.
Challenges and Future Developments
While the initial case reports have been promising, the widespread implementation of accelerometer-based sensor systems in Thoroughbred racing still faces some challenges. Obtaining follow-up information on the horses identified as high-risk has proven difficult, with many trainers not returning calls or maintaining contact regarding the status of their horses.
Additionally, the availability of advanced imaging modalities like PET scanning remains limited, with only a handful of dedicated units available at racetracks. Structural imaging techniques such as MRI and CT, which can provide more detailed information about the extent and nature of any pathologies, are even less accessible in the field.
As the use of these sensor systems expands, ongoing refinement of the algorithms and incorporation of additional data streams, such as angular measurements of pitch, yaw, and roll, may enhance the accuracy of risk assessment. Increased collaboration between racing jurisdictions to build larger, more comprehensive databases of horse stride patterns and injury outcomes will also be crucial for improving the predictive capabilities of these technologies.
Ultimately, the widespread adoption of accelerometer-based sensor systems, coupled with improved access to advanced diagnostics, has the potential to revolutionize the way Thoroughbred racehorses are monitored and cared for. By empowering veterinarians and trainers to identify at-risk horses before catastrophic injuries occur, these innovations can help safeguard the welfare of both equine and human athletes, while also preserving the long-term viability and social license of the Thoroughbred racing industry.
