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Identification of a Modified Wiener-Hammerstein System and Its Application in Electrically Stimulated Paralyzed Skeletal Muscle Modeling

机译:改进的Wiener-Hammerstein系统的鉴定及其在电刺激瘫痪骨骼肌建模中的应用

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摘要

Electrical muscle stimulation demonstrates potential for restoring functional movement and preventing muscle atrophy after spinal cord injury (SCI). Control systems used to optimize delivery of electrical stimulation protocols depend upon mathematical models of paralyzed muscle force outputs. While accurate, the Hill-Huxley-type model is very complex, making it difficult to implement for real-time control. As an alternative, we propose a modified Wiener-Hammerstein system to model the paralyzed skeletal muscle dynamics under electrical stimulus conditions. Experimental data from the soleus muscles of individuals with SCI was used to quantify the model performance. It is shown that the proposed Wiener-Hammerstein system is at least comparable to the Hill-Huxley-type model. On the other hand, the proposed system involves a much smaller number of unknown coefficients. This has substantial advantages in identification algorithm analysis and implementation including computational complexity, convergence and also in real time model implementation for control purposes.
机译:肌肉电刺激显示出在脊髓损伤(SCI)后恢复功能运动和预防肌肉萎缩的潜力。用于优化电刺激方案传递的控制系统取决于瘫痪的肌肉力量输出的数学模型。虽然精确,但Hill-Huxley型模型非常复杂,因此难以实现实时控制。作为替代方案,我们提出了一种经过改进的Wiener-Hammerstein系统,以对电刺激条件下瘫痪的骨骼肌动力学进行建模。来自患有SCI的个体的比目鱼肌的实验数据用于量化模型表现。结果表明,所提出的维纳-汉默斯坦系统至少可以与希尔-赫克斯利型模型进行比较。另一方面,所提出的系统涉及数量少得多的未知系数。这在识别算法的分析和实施中具有很大的优势,包括计算复杂性,收敛性以及在出于控制目的的实时模型实施中。

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