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功能性电刺激与机器人辅助的上肢康复混合协同控制。

Hybrid Cooperative Control of Functional Electrical Stimulation and Robot Assistance for Upper Extremity Rehabilitation.

出版信息

IEEE Trans Biomed Eng. 2024 Sep;71(9):2642-2650. doi: 10.1109/TBME.2024.3384939.

Abstract

OBJECTIVE

Hybrid systems that integrate Functional Electrical Stimulation (FES) and robotic assistance have been proposed in neurorehabilitation to enhance therapeutic benefits. This study focuses on designing a cooperative controller capable of distributing the required torque for movement between robotic actuation and FES, thereby eliminating the need for time-consuming calibration procedures.

METHODS

The control schema comprises three main blocks: a motion generation block that defines the desired trajectory, a motor control block including both a weight compensation feedforward and a feedback impedance controller, and an FES control block, based on trial-by-trial Iterative Learning Control (ILC), that adjusts the stimulation intensity according to a predefined stimulation waveform. The feedforward motor assistance can be dynamically regulated using an allocation factor. Experiments involving 12 healthy volunteers were conducted using a one-degree-of-freedom elbow testbed.

RESULTS

The experimental results showcased the successful integration of Functional Electrical Stimulation (FES) with robotic actuation, ensuring precise trajectory tracking with a Root Mean Square Error (RMSE) below 7°. Notably, allocating more torque to FES led to a 51 % reduction in motor torque. In conditions where FES operated alone, there was poorer tracking performance with an RMSE of 24° and an early onset of muscle fatigue, as evidenced by a reduced number of achieved repetitions. Furthermore, the hybrid approach enabled 100 fatigue-free elbow flexion repetitions, underscoring the effectiveness of cooperative FES-motor control in extending the benefits of FES-induced exercises.

SIGNIFICANCE

This study proposes a flexible approach which can be extended to a multi-degree-of-freedom hybrid system. Furthermore, it underscores the significance of employing a straightforward and adaptable methodology with a rapid calibration procedure, making it easily transferable to clinical applications.

摘要

目的

在神经康复中,已经提出了将功能性电刺激(FES)与机器人辅助相结合的混合系统,以增强治疗效果。本研究专注于设计一种协作控制器,能够在机器人致动和 FES 之间分配运动所需的扭矩,从而无需耗时的校准程序。

方法

控制方案包括三个主要部分:运动生成块,定义期望轨迹;电机控制块,包括重量补偿前馈和反馈阻抗控制器;基于逐次迭代学习控制(ILC)的 FES 控制块,根据预定义的刺激波形调整刺激强度。可以使用分配因子动态调节前馈电机辅助。使用一自由度肘部测试台进行了涉及 12 名健康志愿者的实验。

结果

实验结果展示了 FES 与机器人致动的成功集成,确保了精确的轨迹跟踪,均方根误差(RMSE)低于 7°。值得注意的是,将更多扭矩分配给 FES 会导致电机扭矩减少 51%。在 FES 单独运行的情况下,跟踪性能较差,RMSE 为 24°,肌肉疲劳较早出现,表现为达到的重复次数减少。此外,混合方法能够实现 100 次无疲劳的肘部弯曲重复运动,突出了协作 FES-电机控制在延长 FES 诱导运动益处方面的有效性。

意义

本研究提出了一种灵活的方法,可以扩展到多自由度混合系统。此外,它强调了采用简单、适应和快速校准程序的方法的重要性,使其易于转移到临床应用中。

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