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Kinematic Synergy of Multi-DoF Movement in Upper Limb and Its Application for Rehabilitation Exoskeleton Motion Planning

机译:上肢多自由度运动的运动学协同作用及其对康复外科运动规划的应用

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摘要

It is important for rehabilitation exoskeletons to move with a spatiotemporal motion patterns that well match the upper-limb joint kinematic characteristics. However, few efforts have been made to manipulate the motion control based on human kinematic synergies. This work analyzed the spatiotemporal kinematic synergies of right arm reaching movement and investigated their potential usage in upper limb assistive exoskeleton motion planning. Ten right-handed subjects were asked to reach 10 target button locations placed on a cardboard in front. The kinematic data of right arm were tracked by a motion capture system. Angular velocities over time for shoulder flexion/extension, shoulder abduction/adduction, shoulder internal/external rotation, and elbow flexion/extension were computed. Principal component analysis (PCA) was used to derive kinematic synergies from the reaching task for each subject. We found that the first four synergies can explain more than 94% of the variance. Moreover, the joint coordination patterns were dynamically regulated over time as the number of kinematic synergy (PC) increased. The synergies with different order played different roles in reaching movement. Our results indicated that the low-order synergies represented the overall trend of motion patterns, while the high-order synergies described the fine motions at specific moving phases. A 4-DoF upper limb assistive exoskeleton was modeled in SolidWorks to simulate assistive exoskeleton movement pattern based on kinematic synergy. An exoskeleton Denavit-Hartenberg (D-H) model was established to estimate the exoskeleton moving pattern in reaching tasks. The results further confirmed that kinematic synergies could be used for exoskeleton motion planning, and different principal components contributed to the motion trajectory and end-point accuracy to some extent. The findings of this study may provide novel but simplified strategies for the development of rehabilitation and assistive robotic systems approximating the motion pattern of natural upper-limb motor function.
机译:对于康复外骨骼来说,恢复骨骼骨骼的恢复型运动模式非常重要,这与上肢关节运动特性相匹配。然而,已经采取了很少的努力来操纵基于人类运动学协同作用的运动控制。这项工作分析了右臂伸展运动的时空运动学协同作用,并调查了上肢辅助外骨骼运动规划的潜在用法。要求十个右撇子主题达到10个目标按钮位置放在前面的纸板上。右臂的运动数据由运动捕获系统跟踪。随着时间的推移,角速度随着时间的推移,肩部屈曲/延伸,肩部绑架/内收,肩部内/外旋,肩部弯曲/延伸部。主要成分分析(PCA)用于从每个主题的到达任务中导出运动学协同作用。我们发现前四个协同作用可以解释超过94%的方差。此外,随着运动人数(PC)的数量增加,随着时间的推移,接头协调模式随着时间的推移而动态调节。不同秩序的协同作用在达到运动时发挥了不同的作用。我们的结果表明,低阶协同效应代表了运动模式的总体趋势,而高阶协同效应则描述了特定移动阶段的细动运动。 4-DOF上肢辅助外骨骼在SolidWorks中建模,以模拟基于运动学协同作用的辅助外骨骼运动模式。建立了外骨骼Denavit-Hartenberg(D-H)模型,以估算达到任务的外骨骼移动模式。结果进一步证实,运动协同效应可用于外骨骼运动规划,不同的主要组成部分在某种程度上导致了运动轨迹和终点精度。本研究的结果可以为近似自然上肢运动功能的运动模式的康复和辅助机器人系统提供新颖但简化的策略。

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