Feasibility of manual teach-and-replay and continuous impedance shaping for robotic locomotor training following spinal cord injury
Feasibility of manual teach-and-replay and continuous impedance shaping for robotic locomotor training following spinal cord injury
复制标题
脊髓损伤后机器人运动训练中手动教学和重放以及连续阻抗塑形的可行性
DOI：
10.1109/tbme.2007.910683
复制
发表时间：
2008-01-01
影响因子：
4.6
通讯作者：
Reinkensmeyer, David J.
中科院分区：
文献类型：
--
作者：
Emken, Jeremy L.;Harkema, Susan J.;Reinkensmeyer, David J.
机器人步态训练是脊髓损伤后再训练行走能力的一种新兴技术。这项训练的一个关键挑战是为每位患者确定合适的步进轨迹和辅助水平，因为患者的体型和损伤程度各不相同。在这里，我们展示了一个重量轻但功能强大的机器人如何在手动辅助行走期间记录受试者特定的训练器诱导的腿部轨迹，然后立即回放这些轨迹。受试者特定轨迹的回放减少了训练师在手动辅助期间所需的努力，但仍然为六名慢性脊髓损伤受试者产生了类似的肌肉激活模式。我们还演示了如何通过基于错误的学习规律逐步调整机器人的阻抗。该阻抗整形算法调整了机器人的阻抗，使机器人仅在被测者始终表现出错误的阶跃轨迹区域进行辅助。结果是，受试者的步态变化更大，但仍保持生理步态模式。这些结果是根据个体患者的需要定制机器人步态训练的进一步步骤。
Robotic gait training is an emerging technique for retraining walking ability following spinal cord injury (SCI). A key challenge in this training is determining an appropriate stepping trajectory and level of assistance for each patient, since patients have a wide range of sizes and impairment levels. Here, we demonstrate how a lightweight yet powerful robot can record subject-specific, trainer-induced leg trajectories during manually assisted stepping, then immediately replay those trajectories. Replay of the subject-specific trajectories reduced the effort required by the trainer during manual assistance, yet still generated similar patterns of muscle activation for six subjects with a chronic SCI We also demonstrate how the impedance of the robot can be adjusted on a step-by-step basis with an error-based, learning law. This impedance-shaping algorithm adapted the robot's impedance so that the robot assisted only in the regions of the step trajectory where the subject consistently exhibited errors. The result was that the subjects stepped with greater variability, while still maintaining a physiologic gait pattern. These results are further steps toward tailoring robotic gait training to the needs of individual patients.