BCI R&D Program, Wadsworth Center, New York State Department of Health, Albany, NY, USA.
J Neural Eng. 2009 Dec;6(6):066001. doi: 10.1088/1741-2560/6/6/066001. Epub 2009 Oct 1.
Brain signals can provide the basis for a non-muscular communication and control system, a brain-computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function.
脑信号可以为运动障碍患者提供非肌肉通信和控制系统（脑机接口）的基础。创建脑机接口设备的一种常见方法是使用皮层内微电极记录的信号来解码运动的运动学参数。最近的研究表明，也可以从放置在大脑表面的电极（脑皮层电图（ECoG））记录的信号中准确地解码手部运动的运动学参数。在本研究中，我们通过证明使用人类的 ECoG 信号也可以解码单个手指弯曲的时间过程，并且证明这些弯曲时间过程与运动手指高度相关，从而扩展了这些结果。这些结果为 ECoG 可能成为强大的临床实用脑机接口系统的基础的假设提供了额外的支持，并且还表明 ECoG 可用于研究与运动功能相关的皮层动力学。
