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	NeuroCubeRehab: A pilot study for EEG classification in rehabilitation practice based on spiking neural networks
	Yixiong Chen; Jin Hu; Nikola Kasabov; Zeng-Guang Hou; Long Cheng
	2013
会议日期	Nov, 2013
会议地点	Daegu
国家	South Korea
英文摘要	One of the most important issues among active rehabilitation technique is how to extract the voluntary intention of patient through bio-signals, especially EEG signal. This pilot study investigates the feasibility of utilizing a 3D spiking neural networks-based architecture named NeuCube for EEG data classification in the rehabilitation practice. In this paper, the architecture of the NeuCube is designed and a Functional Electrical Stimulation (FES) rehabilitation scenario is introduced which requires accurate classification of EEG signal to achieve active FES control. Three classes of EEG signals corresponding to three imaginary wrist motions are collected and classified. The NeuCube architecture provides promising classification results, which demonstrates our proposed method is capable of extracting the voluntary intention in the rehabilitation practice.
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/23146]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
推荐引用方式 GB/T 7714	Yixiong Chen,Jin Hu,Nikola Kasabov,et al. NeuroCubeRehab: A pilot study for EEG classification in rehabilitation practice based on spiking neural networks[C]. 见:. Daegu. Nov, 2013.

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