Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan.
Institute of Veterinary Clinical Science, School of Veterinary Medicine, National Taiwan University, Taipei, Taiwan.
BMC Vet Res. 2020 Apr 3;16(1):105. doi: 10.1186/s12917-020-02323-5.
Skin marker-based three-dimensional kinematic gait analysis were commonly used to assess the functional performance and movement biomechanics of the pelvic limb in dogs. Unfortunately, soft tissue artefact would compromise the accuracy of the reproduced pelvic limb kinematics. Multibody kinematics optimization framework was often employed to compensate the soft tissue artefact for a more accurate description of human joint kinematics, but its performance on the determination of canine pelvic limb skeletal kinematics has never been evaluated. This study aimed to evaluate a multibody kinematics optimization framework used for the determination of canine pelvic limb kinematics during gait by comparing its results to those obtained using computed tomography model-based fluoroscopy analysis.
Eight clinically normal dogs were enrolled in the study. Fluoroscopy videos of the stifle joint and skin marker trajectories were acquired when the dogs walked on a treadmill. The pelvic limb kinematics were reconstructed through marker-based multibody kinematics optimization and single-body optimization. The reference kinematics data were derived via a model-based fluoroscopy analysis. The use of multibody kinematics optimization yielded a significantly more accurate estimation of flexion/extension of the hip and stifle joints than the use of single-body optimization. The accuracy of the joint model parameters and the weightings to individual markers both influenced the soft tissue artefact compensation capability.
Multibody kinematics optimization designated for soft tissue artefact compensation was established and evaluated for its performance on canine gait analysis, which provided a further step in more accurately describing sagittal plane kinematics of the hip and stifle joints.
基于皮肤标记的三维运动学步态分析常用于评估犬后肢的功能表现和运动生物力学。然而，软组织伪影会影响后肢运动学的准确性。多刚体运动学优化框架常用于补偿软组织伪影，以更准确地描述人体关节运动学，但它在确定犬后肢骨骼运动学方面的性能尚未得到评估。本研究旨在通过比较基于多刚体运动学优化和基于单刚体优化的方法来评估一种用于确定犬步态时后肢运动学的多刚体运动学优化框架。
本研究纳入了 8 只临床正常的犬。当犬在跑步机上行走时，获取膝关节和皮肤标记轨迹的荧光透视视频。通过基于标记的多刚体运动学优化和单刚体优化来重建后肢运动学。参考运动学数据通过基于模型的荧光透视分析获得。与单刚体优化相比，多刚体运动学优化可更准确地估计髋关节和膝关节的屈伸运动。关节模型参数的准确性和对各个标记的加权都会影响软组织伪影补偿能力。
本研究建立并评估了用于软组织伪影补偿的多刚体运动学优化方法，以进一步更准确地描述髋关节和膝关节的矢状面运动学。
