Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG.
Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG.
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DOI：
10.1109/tnsre.2013.2286955
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发表时间：
2014-05
期刊：
影响因子：
--
通讯作者：
Crone NE
中科院分区：
文献类型：
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作者：
Fifer MS;Hotson G;Wester BA;McMullen DP;Wang Y;Johannes MS;Katyal KD;Helder JB;Para MP;Vogelstein RJ;Anderson WS;Thakor NV;Crone NE
使用来自两名人类受试者的颅内脑电图（iEEG）信号，使用约翰霍普金斯大学应用物理实验室（JHU/APL）的模块化假肢（MPL）（一种灵巧的机器人假肢）实现对伸手和抓握运动的同时神经控制。然后，使用来自一小部分电极的高伽马活性，利用在短的达到和抓握块上训练的模型，在没有进一步适应的情况下，实现了对达到和抓握的独立的在线控制。在任一受试者的三个测试区组中，分类准确性没有下降（p<0.05，单因素方差分析）。在独立执行的外伸和抓握运动期间，（受试者1，受试者2）的平均分类准确度分别为（0.85，0.81）和（0.80，0.96），在同时执行期间，它们分别为（0.83，0.88）和（0.58，0.88）。我们的模型利用了受试者的个体功能神经解剖学知识，用于达到和抓握运动，允许在时间敏感的临床环境中快速获得控制。我们证明了潜在的可行性，验证功能有意义的基于iEEG的控制MPL之前，慢性植入，在此期间，MPL的额外能力可能会被利用进一步的培训。
Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the subject made reaching and grasping movements to identify task-selective electrodes. Independent, online control of reaching and grasping was then achieved using high gamma activity from a small subset of electrodes with a model trained on short blocks of reaching and grasping with no further adaptation. Classification accuracy did not decline (p<0.05, one-way ANOVA) over three blocks of testing in either subject. Mean classification accuracy during independently executed overt reach and grasp movements for (Subject 1, Subject 2) were (0.85, 0.81) and (0.80, 0.96) respectively, and during simultaneous execution they were (0.83, 0.88) and (0.58, 0.88) respectively. Our models leveraged knowledge of the subject's individual functional neuroanatomy for reaching and grasping movements, allowing rapid acquisition of control in a time-sensitive clinical setting. We demonstrate the potential feasibility of verifying functionally meaningful iEEG-based control of the MPL prior to chronic implantation, during which additional capabilities of the MPL might be exploited with further training.