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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:通过神经肌肉电刺激改善人类下肢康复的改进遗传算法进行微调的基于崛起的控制器

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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,已经进行了几项研究表明功能性电刺激(FES)和神经肌肉电刺激(NMES)产生良好的脊髓损伤(SCI)的治疗结果。本文介绍了基于改进的遗传算法(IGA)的微调方法对不确定的非线性系统的一种连续和鲁棒控制技术,所述非线性系统被命名为误差(上升)符号的稳健积分,用于膝关节控制。在理想和非膜病症的三个截瘫和一个健康鉴定患者提供仿真结果。虽然在文献中,本控制器呈现出良好的结果而无需任何精细调整方法,但我们提供了一种改善它的方法,更加努力,通过选择充分选择的SCI患者的疲劳和其他经常发生的问题。上升控制器的增益参数。

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