Faculty of Environmental & Life Sciences, University of Southampton, Southampton, UK.
Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.
Ann Biomed Eng. 2020 May;48(5):1551-1561. doi: 10.1007/s10439-020-02476-2. Epub 2020 Feb 19.
This study assessed the accuracy of marker-based kinematic analysis of the fingers, considering soft tissue artefacts (STA) and marker imaging uncertainty. We collected CT images of the hand from healthy volunteers with fingers in full extension, mid- and full-flexion, including motion capture markers. Bones and markers were segmented and meshed. The bone meshes for each volunteer's scans were aligned using the proximal phalanx to study the proximal interphalangeal joint (PIP), and using the middle phalanx to study the distal interphalangeal joint (DIP). The angle changes between positions were extracted. The HAWK protocol was used to calculate PIP and DIP joint flexion angles in each position based on the marker centroids. Finally the marker locations were 'corrected' relative to the underlying bones, and the flexion angles recalculated. Static and dynamic marker imaging uncertainty was evaluated using a wand. A strong positive correlation was observed between marker- and CT-based joint angle changes with 0.980 and 0.892 regression slopes for PIP and DIP, respectively, and Root Mean Squared Errors below 4°. Notably for the PIP joint, correlation was worsened by STA correction. The 95% imaging uncertainty interval was < ± 1° for joints, and < ± 0.25 mm for segment lengths. In summary, the HAWK marker set's accuracy was characterised for finger joint flexion angle changes in a small group of healthy individuals and static poses, and was found to benefit from skin movements during flexion.
本研究评估了基于标记的手指运动学分析的准确性，考虑了软组织伪影（STA）和标记成像不确定性。我们从手指完全伸展、中弯曲和完全弯曲的健康志愿者中收集手部 CT 图像，包括运动捕捉标记。对骨骼和标记进行分割和网格化。使用近节指骨对齐每个志愿者扫描的骨骼网格，以研究近指间关节（PIP），并使用中节指骨研究远指间关节（DIP）。提取位置之间的角度变化。使用 HAWK 协议根据标记质心计算每个位置的 PIP 和 DIP 关节弯曲角度。最后，相对于基础骨骼“校正”标记位置，并重新计算弯曲角度。使用魔杖评估静态和动态标记成像不确定性。标记和 CT 关节角度变化之间存在很强的正相关性，PIP 和 DIP 的回归斜率分别为 0.980 和 0.892，根均方误差低于 4°。值得注意的是，对于 PIP 关节，STA 校正会使相关性恶化。关节的 95%成像不确定性区间为 < ± 1°，节段长度的 < ± 0.25mm。总之，在一小部分健康个体和静态姿势中，HAWK 标记集的准确性特征是手指关节弯曲角度的变化，并且发现它受益于弯曲过程中的皮肤运动。
