Helen M. S. Davies
Papers
1
Total Citations
15
H-Index
1
About
Dr. Helen M. S. Davies is a pioneering researcher at the intersection of equine biomechanics and artificial intelligence. Her work focuses on developing novel computational methods to analyze equine locomotion, particularly through the application of deep learning to sensor data. Her most cited paper, "The use of deep learning algorithms to predict mechanical strain from linear acceleration and angular rates of motion recorded from a horse hoof during exercise" (2021, 15 citations), represents a significant breakthrough in non-invasive equine health monitoring. This study demonstrated how machine learning can translate simple motion sensor data into accurate predictions of hoof strain, offering a powerful tool for early detection of lameness and injury in performance horses. By bridging the gap between raw sensor outputs and meaningful biomechanical insights, Davies has opened new avenues for real-time, field-based equine welfare assessment. Her work is foundational for researchers and veterinarians seeking to leverage AI for more precise, accessible, and continuous monitoring of equine athletes.
Research Focus
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Top Papers
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