A chronic generalized bi-directional brain-machine interface
A chronic generalized bi-directional brain-machine interface
复制标题
DOI：
10.1088/1741-2560/8/3/036018
复制
发表时间：
2011-06-01
影响因子：
4
通讯作者：
Denison, T. J.
中科院分区：
文献类型：
--
作者：
Rouse, A. G.;Stanslaski, S. R.;Denison, T. J.
设计了一个双向神经接口（NI）系统，并将一个新的神经记录和处理子系统的商业神经刺激器架构的原型。NI系统原型利用现有神经刺激器的系统基础设施，确保在慢性植入环境中可靠运行。除了提供等同治疗功能外，该器械还增加了促进慢性研究的关键要素，例如四个皮质电图/局部场电位放大和频谱分析通道、三轴加速度计、算法处理、基于事件的数据记录以及用于数据上传和算法/配置更新的无线遥测。定制集成的微功率传感器和接口电路有助于在功率受限的设备中扩展操作。原型经过了重要的验证测试，以确保可靠性，并符合IEC-60601协议中CF类仪器的要求。使用用于计算机光标大脑控制的体内非人灵长类动物模型（即脑机接口或BMI），对器械系统处理和辅助分类大脑状态的能力进行了临床前验证。选择灵长类动物BMI模型是因为其能够定量测量来自大脑活动的信号解码性能，该信号解码性能在幅度和光谱内容方面与用于检测疾病状态的其他生物标志物相似（例如，G.帕金森氏病）。该研究原型的一个关键目标是帮助扩大NI技术的临床范围和接受度，特别是实时大脑状态检测。这些技术有可能被推广到运动假体之外，并且正在探索其他神经系统疾病（如运动障碍、中风和癫痫）中未满足的需求。
A bi-directional neural interface (NI) system was designed and prototyped by incorporating a novel neural recording and processing subsystem into a commercial neural stimulator architecture. The NI system prototype leverages the system infrastructure from an existing neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing predicate therapy capabilities, the device adds key elements to facilitate chronic research, such as four channels of electrocortigram/local field potential amplification and spectral analysis, a three-axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom-integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in vivo non-human primate model for brain control of a computer cursor (i.e. brain-machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e. g. Parkinson's disease). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques have the potential to be generalized beyond motor prosthesis, and are being explored for unmet needs in other neurological conditions such as movement disorders, stroke and epilepsy.