A primate model of an intra-cortically controlled FES prosthesis for grasp

描述(申请人提供)：当被问及时，大多数患有四肢瘫痪的脊髓损伤(SCI)患者报告说，重新使用他们的手的能力将比任何其他失去的功能更重要。功能性电刺激(FES)是一项了不起的技术，可以用来使瘫痪患者的肌肉收缩。FES已被用于恢复瘫痪患者的抓握能力。对于恢复灵巧的手运动，FES的主要局限性是无法以足够的力量和特异性激活肌肉，以及瘫痪患者所能产生的控制信号不足。脑机接口(BMI)可以提供必要的控制信号。BMI已经达到了治疗瘫痪患者的神经工程学努力的前沿。然而，尽管BMI技术取得了显著进步，但目前几乎所有的应用程序都仅限于在单一、受限的环境中每天进行几个小时的治疗。目前恢复运动的BMI只能通过机器人或肢体外骨骼来实现，并且没有一个提供对力量的明确控制。这些限制最终将限制患者完全适应这项技术、在白天或晚上的任何时间轻松使用它，以及将它应用于各种行为的能力。通过将BMI技术与FES相结合，我们相信我们可以克服这些限制。我们已经展示了一种独特的BMI，它使用外周神经阻滞来麻痹猴子的手，作为脊髓损伤的模型：我们使用从皮质记录中提取的有关预期肌肉活动的信息来产生FES控制信号，从而允许猴子重新获得对其手腕和手的自愿控制。我们建议使用这个BMI控制的FES模型来恢复猴子受试者长达一个月的全天候手使用。我们将开发自适应的、依赖于状态的解码器，旨在扩大FES BMI将有用的运动行为范围。我们将通过使用用于神经记录和周围神经刺激的新型电极，提高从大脑获得的信息质量和激活肌肉的有效性。最后，我们将开发一种持久的周围神经阻滞，导致长达一个月的瘫痪。我们将通过遥测记录，控制一个完全植入的神经肌肉刺激器，这将使我们有一个前所未有的机会来研究对BMI神经假体的长期适应。我们将研究这种适应带来的行为改善，无论是在猴子自然的家庭笼子行为中，还是在更严格的实验室环境中。我们将研究猴子的自适应和自适应算法之间的相互作用。这项工作将提供关于成年哺乳动物大脑的适应能力的重要基本信息，BMI暴露在多大程度上可以拯救因瘫痪而经历适应不良变化的皮质，以及长期练习在多大程度上改善了BMI的表现。

DESCRIPTION (provided by applicant): When asked, most spinal cords injured (SCI) patients suffering tetraplegia report that regaining the ability to use their hands would be more important than any other lost function. Functional Electrical Stimulation (FES) is a remarkable technology that can be used to cause the muscles of a paralyzed patient to contract. FES has been used to restore grasping to paralyzed patients. The primary limitations of FES for the restoration of dexterous hand movements are the inability to activate muscles with adequate force and specificity, and the inadequacy of the control signals that the paralyzed patient can generate. The Brain Machine Interface (BMI) may provide the necessary control signal. BMIs have reached the forefront of the neural engineering endeavor to treat patients suffering from paralysis. Yet despite remarkable BMI technology advances, virtually all current applications are limited to daily, several-hour sessions in a single, constrained setting. Current BMIs that restore movement do so only through a robot or limb exoskeleton, and none provides explicit control of force. These constraints will ultimately limit patients' ability to adapt fully to the technology, to use it readily at any time of the day or night, and to apply it to a broad range of behaviors. By coupling BMI technology to FES, we believe we can overcome these limitations. We have demonstrated a unique BMI using a peripheral nerve block to paralyze a monkey's hand as a model for SCI: We use information about intended muscle activity extracted from cortical recordings to produce an FES control signals that allows the monkeys to regain voluntary control of their wrist and hand. We propose to use this BMI-controlled FES model to restore round-the-clock hand use to monkey subjects for month-long periods of time. We will develop adaptive, state-dependent decoders designed to broaden the range of motor behaviors for which the FES BMI will be useful. We will improve both the quality of information we can obtain from the brain and the effectiveness with which we can activate muscles by using new types of electrodes for neural recording and peripheral nerve stimulation. Finally, we will develop a long-lasting peripheral nerve block to cause month-long paralysis. We will record telemetrically, to control a fully implanted neuromuscular stimulator that will allow us an unprecedented opportunity to study long-term adaptation to a BMI neuroprosthesis. We will study the behavioral improvement that results from this adaptation both in the monkey's natural home-cage behaviors and in the more constrained lab setting. We will study the interaction between the monkey's adaptation and the adaptive algorithms. This work will provide important basic information about the adaptive capability of the adult, mammalian brain, the extent to which BMI exposure can "rescue" cortex that undergoes maladaptive changes in response to paralysis, and the extent to which long- term practice improves BMI performance.