Four-limb IMU sensors for canine gait analysis
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Canine models of human musculoskeletal diseases, such as Duchenne muscular dystrophy (DMD), are important translational animal models for developing therapies. Musculoskeletal diseases alter gait performance, and gait analysis could provide useful data for diagnosis and evaluating treatment outcomes. Wireless inertial measurement unit (IMU) offers low cost, 3D motion tracking and can be a viable option for musculoskeletal assessment in the canine model. This thesis research aims to develop a four limb IMU sensor system for canine gait analysis. We designed and constructed a four limb sensor mounting system using 3D printing. Custom algorithms were developed to analyze the IMU data and determine stride phase timing. To determine the accuracy of our method, we conducted synchronized gait tests with the GAIT4Dog, a commercially available system. Our algorithm detected the swing start event in both front and hind limbs with high accuracy with a mean error [plus-minus] standard deviation of 0.005 [plus-minus] 0.013 sec and 0.002 [plus-minus] 0.015 sec respectively. The system was then used to compare gait in 3 year old dogs including 7 dystrophic dogs, 3 healthy dogs, and 2 dystrophic dogs treated with gene therapy. We identified a distinct gait feature in dystrophic dogs' front limb linked to their lateral sway motion. This feature was improved in dystrophic dogs that received gene therapy. This novel four limb IMU system could serve as an effective canine gait analysis tool for veterinary applications or translational, preclinical studies in dogs for human musculoskeletal diseases.