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模拟物理人机接口与不同的用户,手和束压力:一个案例研究.

Mingrui Sun, Tomislav Bacek, Dana Kulic

    IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
    |November 9, 2023
    PubMed
    概括

    在物理治疗中精确的机器人辅助需要了解人机联系. 线性弹阻尼器模型最好地捕捉到这些动态,但需要个别调整以获得最佳性能.

    科学领域:

    • 机器人技术 机器人技术 机器人技术
    • 生物力学 生物力学
    • 康复工程 康复工程

    背景情况:

    • 机器人设备为物理治疗和性能增强提供精确的干预交付.
    • 物理人机连接的合规性导致功率传输损失和关节错位,影响有效性.
    • 现有的文献往往忽视了连接动态,假定是刚性链接,这限制了机器人干预的稳定性.

    研究的目的:

    • 调查和确定最佳模型形式和参数,以捕捉人机器人连接动态.
    • 解决了解合规在人机交互中的影响的差距.
    • 提高物理治疗中机器人干预的有效性和稳定性.

    主要方法:

    • 研究了各种模型形式和参数,以表示人机器人连接动态.
    • 收集了不同个体,连接设计 (手) 和手带压力的数据.
    • 分析数据以确定最适合人机接口的动态模型.

    主要成果:

    • 线性弹阻尼器模型成为代表连接动态的最有效的妥协方案.
    • 模型参数在不同个体和束条件之间显示出显著的变化.
    • 个性化参数调整对于准确的建模至关重要.

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    结论:

    • 对人机连接动态的准确建模对于有效的机器人辅助至关重要.
    • 线性弹阻尼器模型提供了一个可行的框架,但需要个性化的校准.
    • 未来的研究应该集中在适应性控制策略上,这些策略应考虑到个人的人机交互参数.