Neuroprosthetic Control of an Anthropomorphic Exoskeleton in Tetraplegics

 描述（由申请人提供）：四肢瘫痪或四肢瘫痪的患者严重残疾。调查发现，上肢功能的恢复是这些患者的优先事项。脑机接口（BMIs）通过将大脑的计算能力与人工假肢系统无缝融合，最终可以恢复上肢的伸手和抓握功能。一个主要的挑战是BMI技术的稳健转换 病人护理。当前方法的两个公认的局限性是记录的不稳定性和本体感受反馈信号的缺乏。这项研究计划旨在进行一项试点临床研究，以测试基于皮层电图（ECoG）的控制的拟人外骨骼四肢瘫痪患者的残留本体感觉。我们特别寻求将BMI技术转化为感觉完整的四肢瘫痪患者的重要子集（例如肌萎缩性侧索硬化症或不完全脊髓损伤）。我们的方法将利用公认的稳定性ECoG记录和自然的感觉反馈所产生的被动运动的主题的手臂由外骨骼。拟议的研究应该通过在最大化神经学习机制和提供自然感觉反馈的条件下优化控制来大大推进翻译工作。

 DESCRIPTION (provided by applicant): Patients with tetraplegia, or paralysis of all four limbs, are severely disabled. Surveys have found that restoration of upper-limb function is a high-priority for such patients. Brain-Machine Interfaces (BMIs) can eventually restore upper-limb reaching and grasping function by seamlessly merging the computational power of the brain with artificial prosthetic systems. A major challenge is robust translation of BMI technology to patient care. Two well-recognized limitations of current approaches are instability of recordings and the lack of proprioceptive feedback signals. This research proposal aims to conduct a pilot clinical study to test electrocorticography (ECoG) based control of an anthropomorphic exoskeleton in tetraplegic patients with residual proprioception. We specifically seek to translate BMI technology to the significant subset of tetraplegic patients with intact sensation (e.g. amyotrophic lateral sclerosis or incomplete spinal cord injury). Our approach would capitalize on both the well-recognized stability of ECoG recordings and the natural sensory feedback generated by passive movements of the subject's arm by the exoskeleton. The proposed research should greatly advance translational efforts by optimizing control under conditions that maximize neural learning mechanisms and provide natural sensory feedback.