Cereatti Andrea, Bonci Tecla, Akbarshahi Massoud, Aminian Kamiar, Barré Arnaud, Begon Mickael, Benoit Daniel L, Charbonnier Caecilia, Dal Maso Fabien, Fantozzi Silvia, Lin Cheng-Chung, Lu Tung-Wu, Pandy Marcus G, Stagni Rita, van den Bogert Antonie J, Camomilla Valentina
POLCOMING Department, Information Engineering Unit, University of Sassari, Sassari, Italy; Dept. of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome "Foro Italico", Rome, Italy.
Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome "Foro Italico", Rome, Italy; Life and Health Sciences, Aston University, Birmingham, United Kingdom.
J Biomech. 2017 Sep 6;62:5-13. doi: 10.1016/j.jbiomech.2017.02.004. Epub 2017 Feb 21.
Soft tissue artefact (STA) represents one of the main obstacles for obtaining accurate and reliable skeletal kinematics from motion capture. Many studies have addressed this issue, yet there is no consensus on the best available bone pose estimator and the expected errors associated with relevant results. Furthermore, results obtained by different authors are difficult to compare due to the high variability and specificity of the phenomenon and the different metrics used to represent these data. Therefore, the aim of this study was twofold: firstly, to propose standards for description of STA; and secondly, to provide illustrative STA data samples for body segments in the upper and lower extremities and for a range of motor tasks specifically, level walking, stair ascent, sit-to-stand, hip- and knee-joint functional movements, cutting motion, running, hopping, arm elevation and functional upper-limb movements. The STA dataset includes motion of the skin markers measured in vivo and ex vivo using stereophotogrammetry as well as motion of the underlying bones measured using invasive or bio-imaging techniques (i.e., X-ray fluoroscopy or MRI). The data are accompanied by a detailed description of the methods used for their acquisition, with information given about their quality as well as characterization of the STA using the proposed standards. The availability of open-access and standard-format STA data will be useful for the evaluation and development of bone pose estimators thus contributing to the advancement of three-dimensional human movement analysis and its translation into the clinical practice and other applications.
软组织伪影（STA）是通过运动捕捉获取准确可靠的骨骼运动学数据的主要障碍之一。许多研究都探讨了这个问题，但对于最佳可用的骨骼姿态估计器以及相关结果的预期误差，尚未达成共识。此外，由于该现象的高度变异性和特异性以及用于表示这些数据的不同度量标准，不同作者获得的结果难以比较。因此，本研究的目的有两个：第一，提出STA的描述标准；第二，提供上肢和下肢身体节段以及一系列特定运动任务（具体为平地行走、上楼梯、从坐到站、髋关节和膝关节功能运动、切入动作、跑步、跳跃、手臂抬高和上肢功能运动）的STA数据示例。STA数据集包括使用立体摄影测量法在体内和体外测量的皮肤标记点的运动，以及使用侵入性或生物成像技术（即X射线荧光透视或MRI）测量的深层骨骼的运动。数据还附带了对其采集方法的详细描述，包括有关其质量的信息以及使用所提出的标准对STA的特征描述。开放获取且格式标准的STA数据的可用性将有助于评估和开发骨骼姿态估计器，从而推动三维人体运动分析的发展及其在临床实践和其他应用中的转化。
