Fang Juan, Haldimann Michael, Riener Robert
IEEE Int Conf Rehabil Robot. 2025 May;2025:514-519. doi: 10.1109/ICORR66766.2025.11062946.
The theory of interlimb neural coupling suggests that arm swing should be integrated into gait training to promote neural control of walking. We previously developed a mobile gait trainer which followed the user during free overground walking. However, it did not provide assistance in the synchronised arm and leg movements. This work aimed to develop a robotic arm module for the mobile gait trainer which offers stiff vertical arm support for balance, provides adaptable arm movement guidance during assisted walking, and allows free arm swing as experienced in daily walking. Based on an analysis of the wrist movement from normal gait, an end-effector-based system was developed, which used a screw drive to produce the vertical wrist movement and a timing belt drive with a force sensor to control the anterior-posterior wrist movement. Position controllers were employed to generate arm swing in passive training. Admittance algorithms were developed for the timing belt drive to generate adaptable horizontal movement. Free movement was produced by simplifying the admittance algorithms to include only a damping term. Preliminary tests showed that the position control algorithms produced arm swing in passive training with an accuracy of $\mathbf{1. 7 8}$ mm vertically and $\mathbf{3. 1 7 ~ m m}$ horizontally. The admittance controller produced adaptable anterior-posterior movement, where the active force modified the range of swing amplitude. The simplified admittance controller enabled the user to move freely with negligible interference from the robotic arm module. The system managed to offer rigid support for balance, to provide assisted arm swing for gait training with adaptable anterior-posterior movement, and to allow free arm swing. Integration of the arm movement with the mobile gait trainer and mechanism for leg movement will be investigated in future work.
肢体间神经耦合理论表明,摆臂动作应纳入步态训练,以促进对行走的神经控制。我们之前开发了一种移动步态训练器,它能在用户自由地面行走时跟随用户。然而,它并未在手臂和腿部同步运动方面提供辅助。这项工作旨在为移动步态训练器开发一个机器人手臂模块,该模块能提供刚性的垂直手臂支撑以保持平衡,在辅助行走时提供适应性的手臂运动引导,并允许像日常行走那样自由摆臂。基于对正常步态中手腕运动的分析,开发了一种基于末端执行器的系统,该系统使用丝杠传动来产生垂直手腕运动,并使用带有力传感器的同步带传动来控制前后手腕运动。在被动训练中采用位置控制器来产生摆臂动作。为同步带传动开发了导纳算法,以产生适应性的水平运动。通过简化导纳算法使其仅包含一个阻尼项来实现自由运动。初步测试表明,位置控制算法在被动训练中产生的摆臂动作,垂直精度为1.78毫米,水平精度为3.17毫米。导纳控制器产生适应性的前后运动,其中作用力改变了摆动幅度范围。简化后的导纳控制器使用户能够自由移动,且机器人手臂模块的干扰可忽略不计。该系统成功地提供了刚性支撑以保持平衡,为步态训练提供了带有适应性前后运动的辅助摆臂,并允许自由摆臂。未来的工作将研究手臂运动与移动步态训练器的集成以及腿部运动机制。