Abstract：
Peripheral nerve stimulation (PNS) is an effective means to elicit sensation for rehabilitation of people with loss of a limb or limb function. While most current PNS paradigms deliver current through single electrode contacts to elicit each tactile percept, multi-contact extraneural electrodes offer the opportunity to deliver PNS with groups of contacts individually or simultaneously. Multi-contact PNS strategies could be advantageous in developing biomimetic PNS paradigms to recreate the natural neural activity during touch, because they may be able to selectively recruit multiple distinct neural populations. We used computational models and optimization approaches to develop a novel biomimetic PNS paradigm that uses interleaved multi-contact (IMC) PNS to approximate the critical neural coding properties underlying touch. The IMC paradigm combines field shaping, in which two contacts are active simultaneously, with pulse-by-pulse contact and parameter variations throughout the touch stimulus. We show in simulation that IMC PNS results in better neural code mimicry than single contact PNS created with the same optimization techniques, and that field steering via two-contact IMC PNS results in better neural code mimicry than one-contact IMC PNS. We also show that IMC PNS results in better neural code mimicry than existing PNS paradigms, including prior biomimetic PNS. Future clinical studies will determine if the IMC paradigm can improve the naturalness and usefulness of sensory feedback for those with neurological disorders.
摘要：
周围神经刺激（PNS）是引起肢体或肢体功能丧失的人康复的有效手段。虽然大多数当前的PNS范例通过单电极触点提供电流以引起每个触觉感知，多触点外部电极提供了单独或同时递送具有触点组的PNS的机会。多接触PNS策略可能有利于开发仿生PNS范例，以重建触摸过程中的自然神经活动，因为它们可能能够选择性地招募多种不同的神经群体。我们使用计算模型和优化方法来开发一种新颖的仿生PNS范例，该范例使用交错多接触（IMC）PNS来近似触摸的关键神经编码特性。IMC范式结合了场整形，其中两个触点同时激活，在整个触摸刺激中具有逐脉冲接触和参数变化。我们在仿真中表明，IMCPNS比使用相同优化技术创建的单接触PNS产生更好的神经代码模仿，并且通过双接触式IMCPNS进行场控制比单接触式IMCPNS产生更好的神经代码模仿。我们还表明，IMCPNS比现有的PNS范式产生更好的神经代码模仿，包括先前的仿生PNS。未来的临床研究将确定IMC范式是否可以改善神经系统疾病患者的感觉反馈的自然性和实用性。
