Decoding flexion of individual fingers using electrocorticographic signals in humans.

Decoding flexion of individual fingers using electrocorticographic signals in humans.
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DOI:
10.1088/1741-2560/6/6/066001
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发表时间:
2009-12
影响因子:
4
通讯作者:
Schalk G
Schalk G
中科院分区:
工程技术2区
文献类型:
--
作者:
Kubánek J;Miller KJ;Ojemann JG;Wolpaw JR;Schalk G

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大脑信号可以为有运动障碍的人提供非肌肉交流和控制系统的基础,即脑机接口(BCI)。制造脑机接口设备的一种常见方法是使用皮质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,手部运动的运动学参数也可以从放置在大脑表面的电极记录的信号中准确解码(皮层脑电图仪)。在目前的研究中,我们扩展了这些结果,证明了使用人类的ECoG信号也可以解码单个手指屈曲的时间进程,并表明这些屈曲时间进程高度特定于移动的手指。这些结果进一步支持了ECoG可以作为强大的临床实用BCI系统的基础的假设,也表明ECoG在研究与运动功能相关的皮质动力学方面是有用的。
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.
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