Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device

Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device
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DOI:
10.1109/icra.2019.8794416
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发表时间:
2019-02
期刊:
2019 International Conference on Robotics and Automation (ICRA)
影响因子:
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通讯作者:
A. Kalinowska;Thomas A. Berrueta;A. Zoss;T. Murphey
A. Kalinowska;Thomas A. Berrueta;A. Zoss;T. Murphey
中科院分区:
其他
文献类型:
--
作者:
A. Kalinowska;Thomas A. Berrueta;A. Zoss;T. Murphey

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由于其非线性动力学的不连续性,诸如双足步行者之类的混合系统(例如双足动物)受到挑战。很难控制。我们提出了一种允许使用数据驱动分析实时确定系统的混合模式。数据驱动的动态标识完全基于两个示例,即在第一个示例的情况下使用两个示例。混合滑移模型,然后在第二个示例中成功使用它们进行控制。我们选择的接触事件,例如脚跟罢工和脚趾,仅使用膝盖和臀部关节的运动员数据,这对于在我们的算法期间提供在线帮助,这可能是特别有用的。假设步态结构或步态相变,以这种灵活性,特定于障碍的康复为健康和病理步态的分割。可以设计策略或援助。
Hybrid systems, such as bipedal walkers, are challenging to control because of discontinuities in their nonlinear dynamics. Little can be predicted about the systems’ evolution without modeling the guard conditions that govern transitions between hybrid modes, so even systems with reliable state sensing can be difficult to control. We propose an algorithm that allows for determining the hybrid mode of a system in real-time using data-driven analysis. The algorithm is used with data-driven dynamics identification to enable model predictive control based entirely on data. Two examples—a simulated hopper and experimental data from a bipedal walker—are used. In the context of the first example, we are able to closely approximate the dynamics of a hybrid SLIP model and then successfully use them for control in simulation. In the second example, we demonstrate gait partitioning of human walking data, accurately differentiating between stance and swing, as well as selected subphases of swing. We identify contact events, such as heel strike and toe-off, without a contact sensor using only kinematics data from the knee and hip joints, which could be particularly useful in providing online assistance during walking. Our algorithm does not assume a predefined gait structure or gait phase transitions, lending itself to segmentation of both healthy and pathological gaits. With this flexibility, impairment-specific rehabilitation strategies or assistance could be designed.