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基于 Vicon 运动捕捉系统的肩部复合体改良运动学模型:带浮动中心的广义 GH 关节。

A Modified Kinematic Model of Shoulder Complex Based on Vicon Motion Capturing System: Generalized GH Joint with Floating Centre.

机构信息

Beijing Key Laboratory of Advanced Manufacturing Technology, Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China.

出版信息

Sensors (Basel). 2020 Jul 2;20(13):3713. doi: 10.3390/s20133713.

Abstract

Due to the complex coupling motion of shoulder mechanism, only a small amount of quantitative information is available in the existing literature, although various kinematic models of the shoulder complex have been proposed. This study focused on the specific motion coupling relationship between glenohumeral (GH) joint center displacement variable quantity relative to the thorax coordinate system and humeral elevation angle to describe the shoulder complex. The mechanism model of shoulder complex was proposed with an algorithm designed. Subsequently, twelve healthy subjects performed right arm raising, lowering, as well as raising and lowering (RAL) movements in sixteen elevation planes, and the motion information of the markers attached to the thorax, scapula, and humerus was captured by using Vicon motion capturing system. Then, experimental data was processed and the generalized GH joint with floating center was quantized. Simultaneously, different coupling characteristics were detected during humerus raising as well as lowering movements. The motion coupling relationships in different phases were acquired, and a modified kinematic model was established, with the description of overall motion characteristics of shoulder complex validated by comparing the results with a prior kinematic model from literature, showing enough accuracy for the design of upper limb rehabilitation robots.

摘要

由于肩部机制的复杂耦合运动,尽管已经提出了各种肩部复合体的运动学模型,但现有的文献中只有少量定量信息。本研究侧重于描述肩部复合体的肱骨头关节中心相对于胸腔坐标系的位移变量和肱骨抬高角度之间的特定运动耦合关系。提出了肩部复合体的机械模型,并设计了相应的算法。随后,12 名健康受试者在 16 个提升平面上进行了右臂提升、降低以及提升和降低(RAL)运动,使用 Vicon 运动捕捉系统捕捉附着在胸腔、肩胛骨和肱骨上的标记的运动信息。然后,对实验数据进行处理并对浮动中心的广义 GH 关节进行量化。同时,在肱骨提升和降低运动过程中检测到不同的耦合特征。获取不同阶段的运动耦合关系,并建立一个改进的运动学模型,通过与文献中的先前运动学模型进行比较来验证肩部复合体整体运动特征的描述,为上肢康复机器人的设计提供足够的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67f5/7374450/ec4a58c72410/sensors-20-03713-g001.jpg

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