Data-Driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury.
Data-Driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury.
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DOI：
10.1109/tnsre.2023.3272929
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发表时间：
2023
影响因子：
4.9
通讯作者：
Schearer, Eric M. M.
中科院分区：
文献类型：
--
作者：
Wolf, Derek N. N.;van den Bogert, Antonie J. J.;Schearer, Eric M. M.
关键词：
功能电刺激（FES）是一种很有前途的技术，可以恢复由脊髓损伤（SCI）引起的上肢瘫痪患者的伸展运动。然而，脊髓损伤患者有限的肌肉能力使得实现fes驱动的到达变得困难。我们开发了一种新的轨迹优化方法，使用实验测量的肌肉能力数据来寻找可行的到达轨迹。在一个基于现实生活中脊髓损伤个体的模拟中，我们将我们的方法与试图遵循朴素的直接到达目标的路径进行了比较。我们用三种常用的控制结构测试了轨迹规划器：反馈、前馈反馈和模型预测控制。总体而言，轨迹优化提高了前馈-反馈和模型预测控制器达到目标的能力和精度（p < 0.001）。为了提高fes驱动的到达性能，需要实际实施弹道优化方法。
Functional electrical stimulation (FES) is a promising technology for restoring reaching motions to individuals with upper-limb paralysis caused by a spinal cord injury (SCI). However, the limited muscle capabilities of an individual with SCI have made achieving FES-driven reaching difficult. We developed a novel trajectory optimization method that used experimentally measured muscle capability data to find feasible reaching trajectories. In a simulation based on a real-life individual with SCI, we compared our method to attempting to follow naive direct-to-target paths. We tested our trajectory planner with three control structures that are commonly used in applied FES: feedback, feedforward-feedback, and model predictive control. Overall, trajectory optimization improved the ability to reach targets and improved the accuracy for the feedforward-feedback and model predictive controllers (p < 0.001). The trajectory optimization method should be practically implemented to improve the FES-driven reaching performance.