Hand Motion Capture from a 3D Leap Motion Controller for a Musculoskeletal Dynamic Simulation.
Hand Motion Capture from a 3D Leap Motion Controller for a Musculoskeletal Dynamic Simulation.
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DOI：
10.3390/s21041199
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发表时间：
2021-02-08
期刊：
影响因子：
--
通讯作者：
Engelhardt L
中科院分区：
文献类型：
--
作者：
Fonk R;Schneeweiss S;Simon U;Engelhardt L
任何人建模系统™(AMS)是一个使用逆动力学分析的肌肉骨骼软件模拟解决方案。它能够确定给定身体运动的肌肉和关节力量。个人运动的记录和转移到AMS是一个复杂和漫长的过程。研究表明，非接触式、可视化的Leap运动控制器(LMC)为手部跟踪提供了具有临床意义的运动数据。因此，这项研究的目的是将LMC手部运动数据整合到AMS中，以改进记录手部运动的过程。在LMC和AMS之间开发了一个基于Python的接口，称为ROSE Motion。该解决方案将运动数据记录并保存为Biovision Hierarchy(BVH)数据和AnyScript向量文件，以导入到AMS模拟中。通过使用AnyPyTools库，可以从任何人处设置模拟参数、自动启动计算和获取结果。建议的工具为肘部、手部和手指的移动提供了一种快速且易于使用的记录解决方案。功能包括动画、剪切/编辑、导出运动，以及远程控制AMS以分析和呈现肌肉骨骼模拟结果。将运动跟踪结果与前人的研究结果进行比较，发现使用LMC时存在的问题限制了运动数据的准确性。然而，与基于标记的运动捕捉相比，快速的实验设置和直观且快速的运动数据编辑加强了如本文所示的无标记系统的使用。
The AnyBody Modeling System™ (AMS) is a musculoskeletal software simulation solution using inverse dynamics analysis. It enables the determination of muscle and joint forces for a given bodily motion. The recording of the individual movement and the transfer into the AMS is a complex and protracted process. Researches indicated that the contactless, visual Leap Motion Controller (LMC) provides clinically meaningful motion data for hand tracking. Therefore, the aim of this study was to integrate the LMC hand motion data into the AMS in order to improve the process of recording a hand movement. A Python-based interface between the LMC and the AMS, termed ROSE Motion, was developed. This solution records and saves the data of the movement as Biovision Hierarchy (BVH) data and AnyScript vector files that are imported into the AMS simulation. Setting simulation parameters, initiating the calculation automatically, and fetching results is implemented by using the AnyPyTools library from AnyBody. The proposed tool offers a rapid and easy-to-use recording solution for elbow, hand, and finger movements. Features include animation, cutting/editing, exporting the motion, and remote controlling the AMS for the analysis and presentation of musculoskeletal simulation results. Comparing the motion tracking results with previous studies, covering problems when using the LMC limit the correctness of the motion data. However, fast experimental setup and intuitive and rapid motion data editing strengthen the use of marker less systems as the herein presented compared to marker based motion capturing.
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影响因子：
2.2
作者：
Iosa, Marco;Morone, Giovanni;Paolucci, Stefano
通讯作者：
Paolucci, Stefano
DOI：
10.3390/s18030834
发表时间：
2018-03-10
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
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通讯作者：
Spezialetti M
影响因子：
4.6
作者：
Delp, Scott L.;Anderson, Frank C.;Thelen, Darryl G.
通讯作者：
Thelen, Darryl G.
影响因子：
3.7
作者：
Niechwiej-Szwedo E;Gonzalez D;Nouredanesh M;Tung J
通讯作者：
Tung J
DOI：
10.3390/s18103230
发表时间：
2018-09-25
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Nizamis K;Rijken NHM;Mendes A;Janssen MMHP;Bergsma A;Koopman BFJM
通讯作者：
Koopman BFJM