Developing Software for Gait Analysis

SUMMARY: Researchers will develop a new equine gait analysis software to assessadaptations in movement and muscle activity.

THE PROBLEM: Lameness is the most common reason for equine veterinary examination and represents the leading cause of mortality and/or termination of athletic careers in horses. Historically, lameness examination relies on visual assessment of movement asymmetries due to adaptive strategies to unload the lame limb. Several commercial equine gait analysis (EGA) systems have been developed that use wearable motion sensing technology (IMU) to quantify the movement asymmetries that a veterinarian visually assesses. Although these systems are increasingly used by veterinarians to aid lameness diagnosis, none currently have the capacity to measure the neuromuscular contribution that facilitates these adaptations, which can be detected using non-invasive surface electromyography (sEMG). Unfortunately, veterinarians often lack the specialist knowledge, equipment and time required to acquire, analyze, and interpret sEMG data. As such, there is a need to develop a user-friendly EGA system that employs both motion and sEMG sensing technology to simultaneously quantify adaptations in movement and muscle function, while automating the analysis procedure to provide a more comprehensive diagnostic tool for objective lameness-detection.

THE PROJECT: Recently, through a Morris Animal Foundation grant, the team showed that non-invasive sEMG can detect muscular adaptations to lameness, offering a potential diagnostic tool. Delsys Inc., the worldwide leader in wearable sEMG sensor technology, manufactures sensors with a unique capability to capture both sEMG and IMU data, but associated software for turnkey EGA is not available. Thus, as a first step in the development of a novel EGA system, the proposed proof-of-concept study will investigate whether the complex and time-consuming nature of equine sEMG and IMU signal processing and analysis can be translated into a Python EGA package that automates these steps without sacrificing the consistency or accuracy of outcome measures for quantifying lameness.

POTENTIAL IMPACT: This research could make advanced sEMG technology accessible to practicing veterinarians in the field, which in turn can improve the care of horses.

Projected End Date: 2/28/26