Department of Veterinary Clinical Sciences, College Veterinary Medicine, University of Minnesota, Saint Paul, MN.
K-9 in Motion LLC, Cottage Grove, MN.
Am J Vet Res. 2023 Jan 23;84(3). doi: 10.2460/ajvr.22.10.0178. Print 2023 Mar 1.
To explore relationships between 9-axis inertial measurement unit (IMU) output and activities of varying intensity in dogs of various sizes.
20 healthy, agility course-trained dogs of various ages and sizes.
Height, weight, body condition score, age, length from IMU to the ischium, and height of IMU to the floor were recorded. Dogs performed a series of activities (rest, walk, trot, and agility course) while wearing the IMU device. IMU and video output were reviewed by independent investigators. Correlations and multiple regression models were used to explore relationships between independent variables and IMU output.
Calibration demonstrated excellent correlation and concordance between IMUs (intraclass correlation > 0.9) and that the IMUs reliably measured a known acceleration (gravity at rest). Resultant vector magnitude {sqrt[(x^2) + (y^2) + (z^2)]} normalized to body size was calculated from the data. IMU output clearly discriminates between activities of varying intensity in the dog.
The inability to accurately measure chronic pain is a barrier to the development of new, or critical evaluation of, therapeutics. Activity monitors (AM) may be the ideal diagnostic target since they are small and provide objective data that can be collected while the pet remains in its natural environment. These results demonstrate the concurrent and predictive validity of the IMU tested. Our long-range goal is to validate an open-source algorithm for the IMU so activity in a pet's natural environment can be used as an outcome measure in future studies.
探索 9 轴惯性测量单元 (IMU) 输出与不同体型犬不同强度活动之间的关系。
20 只不同年龄和体型的健康、接受过敏捷课程训练的犬。
记录犬的身高、体重、体况评分、年龄、从 IMU 到坐骨的长度以及 IMU 到地面的高度。犬在佩戴 IMU 设备的情况下进行一系列活动（休息、散步、小跑和敏捷课程）。由独立调查员审查 IMU 和视频输出。使用相关和多元回归模型来探索自变量与 IMU 输出之间的关系。
校准证明了 IMU 之间具有极好的相关性和一致性（组内相关系数>0.9），并且 IMU 可靠地测量了已知的加速度（休息时的重力）。从数据中计算出归一化到体型的结果向量幅度 {sqrt[(x^2) + (y^2) + (z^2)]}。IMU 输出清楚地区分了犬不同强度的活动。
无法准确测量慢性疼痛是新疗法开发或关键评估的障碍。活动监测器 (AM) 可能是理想的诊断目标，因为它们体积小，提供客观数据，可以在宠物处于其自然环境时收集。这些结果证明了经过测试的 IMU 的同时和预测有效性。我们的长期目标是验证 IMU 的开源算法，以便在未来的研究中可以将宠物自然环境中的活动用作结果测量。
