BACKGROUND Leg amputees suffer the lack of sensory feedback from a prosthesis, which is connected to their low confidence during walking, falls and low mobility. Electrical peripheral nerve stimulation (ePNS) of upper-limb amputee's residual nerves has shown the ability to restore the sensations from the missing limb via intraneural (TIME) and epineural (FINE) neural interfaces. Physiologically plausible stimulation protocols targeting lower limb sciatic nerve hold promise to induce sensory feedback restoration that should facilitate close-to-natural sensorimotor integration and therefore walking corrections. The sciatic nerve, innervating the foot and lower leg, has very different dimensions in respect to upper-limb nerves. Therefore, there is a need to develop a computational model of its behavior in response to the ePNS. METHODS We employed a hybrid FEM-NEURON model framework for the development of anatomically correct sciatic nerve model. Based on histological images of two distinct sciatic nerve cross-sections, we reconstructed accurate FEM models for testing neural interfaces. Two different electrode types (based on TIME and FINE) with multiple active sites configurations were tested and evaluated for efficiency (selective recruitment of fascicles). We also investigated different policies of stimulation (monopolar and bipolar), as well as the optimal number of implants. Additionally, we optimized the existing simulation framework significantly reducing the computational load. RESULTS The main findings achieved through our modelling study include electrode manufacturing and surgical placement indications, together with beneficial stimulation policy of use. It results that TIME electrodes with 20 active sites are optimal for lower limb and the same number has been obtained for FINE electrodes. To interface the huge sciatic nerve, model indicates that 3 TIMEs is the optimal number of surgically implanted electrodes. Through the bipolar policy of stimulation, all studied configurations were gaining in the efficiency. Also, an indication for the optimized computation is given, which decreased the computation time by 80%. CONCLUSIONS This computational model suggests the optimal interfaces to use in human subjects with lower limb amputation, their surgical placement and beneficial bipolar policy of stimulation. It will potentially enable the clinical translation of the sensory neuroprosthetics towards the lower limb applications.

中文翻译：

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设计下肢感觉神经假体神经接口的计算模型。


背景技术腿部截肢者缺乏来自假肢的感觉反馈，这与他们在行走、跌倒和行动不便时信心不足有关。上肢截肢者残余神经的电周围神经刺激 (ePNS) 已显示出能够通过神经内 (TIME) 和神经外 (FINE) 神经接口恢复缺失肢体的感觉。针对下肢坐骨神经的生理上合理的刺激方案有望诱导感觉反馈恢复，从而促进接近自然的感觉运动整合，从而促进步行矫正。支配脚和小腿的坐骨神经与上肢神经的尺寸非常不同。因此，需要开发一个响应 ePNS 的行为计算模型。方法我们采用混合 FEM-NEURON 模型框架来开发解剖学上正确的坐骨神经模型。基于两个不同坐骨神经横截面的组织学图像，我们重建了用于测试神经接口的精确 FEM 模型。测试并评估了具有多个活性位点配置的两种不同电极类型（基于 TIME 和 FINE）的效率（束的选择性募集）。我们还研究了不同的刺激政策（单极和双极）以及最佳植入数量。此外，我们优化了现有的模拟框架，显着减少了计算负载。结果通过我们的建模研究获得的主要结果包括电极制造和手术放置适应症，以及有益的刺激使用政策。 结果表明，具有 20 个活性位点的 TIME 电极最适合下肢，并且 FINE 电极也获得了相同数量的电极。为了连接巨大的坐骨神经，模型表明 3 次是手术植入电极的最佳数量。通过双极刺激政策，所有研究的配置都在提高效率。此外，还给出了优化计算的指示，将计算时间减少了 80%。结论 该计算模型提出了用于下肢截肢人类受试者的最佳界面、手术放置和有益的双极刺激策略。它有可能使感觉神经假体临床转化为下肢应用。