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A RISE-based Controller Fine-tuned by an Improved Genetic Algorithm for Human Lower Limb Rehabilitation via Neuromuscular Electrical Stimulation

机译:一种基于RISE的控制器,通过神经肌肉电刺激对人类下肢康复进行了改进的遗传算法进行了微调

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In the last few years, several studies have been carried out showing that Functional Electrical Stimulation (FES) and Neuromuscular Electrical Stimulation (NMES) produce good therapeutic results in patients with Spinal Cord Injury (SCI). This paper presents the proposal of a fine-tuning method based on an Improved Genetic Algorithm (IGA) to a continuous and robust control technique for uncertain nonlinear systems named Robust Integral of the Sign of the Error (RISE), for knee joint control. Simulation results are provided for three paraplegic and one healthy identified patients on ideal and nonideal conditions. Although in the literature this controller presents good results without any fine tuning method, we provide an approach to improve it, even more, believing on the minimization of fatigue and other problems that often occurs in SCI patients treated with FES/NMES, by selecting adequately the gain parameters of the RISE controller.
机译:在过去的几年中,已经进行了一些研究,表明功能性电刺激(FES)和神经肌肉电刺激(NMES)在脊髓损伤(SCI)患者中产生了良好的治疗效果。本文提出了一种基于改进遗传算法(IGA)的微调方法的建议,该方法针对一种称为误差符号的鲁棒积分(RISE)的不确定非线性系统的连续且鲁棒的控制技术,用于膝关节控制。在理想和非理想条件下,为三名截瘫患者和一名健康确定的患者提供了模拟结果。尽管在文献中该控制器礼物而没有任何微调方法的良好的结果,我们提供一种方法来改进它,甚至更多,相信对疲劳和其他问题的最小化,往往发生与FES / NMES处理,通过适当地选择SCI患者RISE控制器的增益参数。

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