Background. Robotic locomotion rehabilitation systems have been used for gait training in patients who have had a stroke. Most commercialized systems allow patients to perform simple exercises such as balancing or level walking, but an additional function such as stair-walk training is required to provide a wide range of recovery cycle rehabilitation. In this study, we analyzed stair-gait patterns and applied the result to a robotic rehabilitation system that can provide a vertical motion of footplates. Methods. To obtain applicable data for the robotic system with vertically movable footplates, stair-walk action was measured using an optical marker-based motion capture system. The spatial position data of joints during stair walking was obtained from six healthy adults who participated in the experiment. The measured marker data were converted into joint kinematic data by using an algorithm that included resampling and normalization. The spatial position data are represented as angular trajectories and the relative displacement of each joint on the anatomical sagittal plane and movements of hip joints on the anatomical transverse plane. Results. The average range of motion (ROM) of each joint was estimated as () at the hip, at the knee, and at the ankle during ascent and as at the hip, at the knee, and at the ankle during descent. Additionally, we attempted to create a more natural stair-gait pattern by analyzing the movement of the hip on the anatomical transverse plane. The hip movements were estimated to within and for hip translation and to within and for hip rotation during stair ascent and stair descent, respectively. Conclusions. Based on the results, standard patterns of stair ascent and stair descent were derived and applied to a lower-limb rehabilitation robot with vertically movable footplates. The relative trajectory from the experiment ascertained that the function of stair walking in the robotic system properly worked within a normal ROM.

中文翻译：

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用于改进机器人运动康复系统的楼梯行走步态模式的测量与分析。

背景。机器人运动康复系统已用于中风患者的步态训练。大多数商业化系统允许患者进行简单的锻炼，如平衡或水平行走，但需要额外的功能，如楼梯行走训练，以提供广泛的恢复周期康复。在这项研究中，我们分析了楼梯步态模式并将结果应用于可以提供踏板垂直运动的机器人康复系统。方法. 为了获得具有垂直可移动踏板的机器人系统的适用数据，使用基于光学标记的运动捕捉系统测量楼梯行走动作。楼梯行走时关节的空间位置数据来自参与实验的 6 名健康成年人。通过使用包括重采样和归一化的算法将测量的标记数据转换为关节运动学数据。空间位置数据表示为角度轨迹和每个关节在解剖矢状面上的相对位移以及髋关节在解剖横切面上的运动。结果。每个关节的平均运动范围（ROM）估计为（)在臀部，在膝盖处，并且在上升过程中的脚踝处在臀部，在膝盖处，并且在下降过程中的脚踝处。此外，我们试图通过分析臀部在解剖横向平面上的运动来创建更自然的楼梯步态模式。在上楼梯和下楼梯期间，髋关节运动被估计为髋关节内和髋部平移以及髋关节内和旋转。结论。根据结果​​，推导出楼梯上升和楼梯下降的标准模式，并将其应用于具有可垂直移动踏板的下肢康复机器人。实验的相对轨迹确定机器人系统中的楼梯行走功能在正常 ROM 内正常工作。