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基于上肢协同作用的腕部自主性:一项初步研究。

Wrist autonomy based on upper-limb synergy: a pilot study.

作者信息

Peng Chunhao, Yang Dapeng, Ge Zhe, Liu Hong

机构信息

State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150080, China.

Artificial Intelligence Laboratory, Harbin Institute of Technology, Harbin, 150080, China.

出版信息

Med Biol Eng Comput. 2023 May;61(5):1149-1166. doi: 10.1007/s11517-023-02783-5. Epub 2023 Jan 23.

Abstract

Incorporating an electrically powered wrist can largely improve the dexterity of a prosthetic hand when grasping various objects; however, it also intensifies the difficulty of the hand's operation due to the introduction of extra degrees of freedom (DOFs). The mechanism of multi-joint synergy in human body movements provides a new sight to solve this problem. In this paper, focusing on four typical manipulation activities of daily life (ADLs), 10 upper-limb joint angles were collected and analyzed first to verify the existence of synergy. Then, a linear regression model was established to predict the wrist rotation angle from the shoulder and elbow joints, which can be directly used as a control reference for achieving wrist autonomy. For both healthy and amputee subjects, experimental platforms were established and control tests were conducted, wherein the task completion time and compensatory movement during the four ADLs were evaluated. The results show that our synergy-based wrist autonomy method can effectively improve the completion efficiency of multiple ADLs without increasing the control complexity. Also, it can significantly reduce the compensatory movements of multiple joints compared to traditional prostheses using an idle wrist.

摘要

加入电动手腕在抓握各种物体时可大幅提高假手的灵活性;然而,由于引入了额外的自由度,这也增加了手部操作的难度。人体运动中的多关节协同机制为解决这一问题提供了新的视角。本文聚焦于日常生活中的四种典型操作活动,首先收集并分析了10个上肢关节角度以验证协同作用的存在。然后,建立了一个线性回归模型,用于从肩关节和肘关节预测手腕旋转角度,该模型可直接用作实现手腕自主性的控制参考。针对健康受试者和截肢者都建立了实验平台并进行了控制测试,评估了四种日常生活活动中的任务完成时间和代偿运动。结果表明,我们基于协同作用的手腕自主性方法能够在不增加控制复杂性的情况下有效提高多种日常生活活动的完成效率。此外,与使用闲置手腕的传统假肢相比,它还能显著减少多个关节的代偿运动。

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