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Synthesis of optimal electrical stimulation patterns for functional motion restoration: applied to spinal cord-injured patients

机译:用于功能性运动恢复的最佳电刺激模式的合成:应用于脊髓损伤的患者

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摘要

We investigated the synthesis of electrical stimulation patterns for functional movement restoration in human paralyzed limbs. We considered the knee joint system, co-activated by the stimulated quadriceps and hamstring muscles. This synthesis is based on optimized functional electrical stimulation (FES) patterns to minimize muscular energy consumption and movement efficiency criteria. This two-part work includes a multi-scale physiological muscle model, based on Huxley’s formulation. In the simulation, three synthesis strategies were investigated and compared in terms of muscular energy consumption and co-contraction levels. In the experimental validation, the synthesized FES patterns were carried out on the quadriceps-knee joint system of four complete spinal cord injured subjects. Surface stimulation was applied to all subjects, except for one FES-implanted subject who received neural stimulation. In each experimental validation, the model was adapted to the subject through a parameter identification procedure. Simulation results were successful and showed high co-contraction levels when reference trajectories were tracked. Experimental validation results were encouraging, as the desired and measured trajectories showed good agreement, with an 8.4 % rms error in a subject without substantial time-varying behavior. We updated the maximal isometric force in the model to account for time-varying behavior, which improved the average rms errors from 31.4 to 13.9 % for all subjects.
机译:我们调查了人类瘫痪肢体功能性运动恢复的电刺激模式的合成。我们考虑了膝关节系统,该系统由受刺激的股四头肌和绳肌共同激活。该合成基于优化的功能性电刺激(FES)模式,以最大程度地减少肌肉能量消耗和运动效率标准。这项由两部分组成的工作包括一个基于Huxley公式的多尺度生理肌肉模型。在模拟中,研究了三种合成策略,并根据肌肉能量消耗和共收缩水平进行了比较。在实验验证中,在四名完全脊髓损伤的受试者的股四头肌-膝关节系统上进行了合成的FES模式。除一名接受神经刺激的FES植入受试者外,所有受试者均实施了表面刺激。在每次实验验证中,都通过参数识别程序使模型适应对象。仿真结果是成功的,并且在跟踪参考轨迹时显示出较高的共收缩水平。实验验证结果令人鼓舞,因为所需的轨迹和测量的轨迹显示出良好的一致性,受试者的均方根误差为8.4%,而没有明显的时变行为。我们更新了模型中的最大等距力以解决随时间变化的行为,这将所有受试者的平均均方根误差从31.4%提高到13.9%。

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