Sheep treadmill and real-life walking kinematic analysis using novel wearable-based method

Introduction Gait analysis has been extensively used in humans to study long-term neuromotor changes resulting from pathology. To improve our understanding and treatment of diseases, sheep particularly have become a commonplace animal model for the study and analysis of neuromotor and functional processes. Currently, there is no kinematic analysis method that can measure sheep gait over an extended period outside of the laboratory setting. We therefore present a novel approach for the kinematic assessment of sheep walking using wearable technologies. Methods Comparative data were first collected from one sheep walking at three different speeds on a treadmill. Subsequently, wearable measurement units, ZurichMOVE, were placed on each limb to estimate stance phase percentage, stride time, stride length, and speed. These metrics were compared against motion capture data, and the agreement between the two methods was calculated. In a second testing setup, nine sheep, again equipped with four ZurichMOVE sensors, walked along the corridor, accompanied by another sheep and an experimenter. The same metrics were calculated. Results The wearables could detect gait events on the treadmill with a time error ranging from 0.6% to 2.2% of the average stride time. The stance phase percentage as well as the stride time was in excellent agreement (from 80% to 100%) with motion capture. The stride length and speed showed an offset with the true values but were still in agreement. Discussion Wearable-based methods offer promising perspectives to assess sheep walking kinematics in a clinical context.