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	A Control System of Lower Limb Exoskeleton Robots Based on Motor Imagery
	Zhouyang Wang; Can Wang; Xinyu Wu; Guizhong Wu
	2017
会议地点	中国澳门
英文摘要	In this paper, we have developed an asynchronous brain–computer interface (BCI)-based lower limb exoskeleton control system based on motor imagery (MI). By decoding electroencephalography (EEG) signals in real-time, users were able to walk forward, sit down, and stand up while wearing the exoskeleton. EEG feature vectors associated with the motor imagery were extracted from the filtered EEG signals with common spatial patterns (CSP) method. And support vector machine (SVM) was employed to address an EEG-based three - class motor imagery classification task. Overall, four healthy subjects participated in the experiment to evaluate performance. To achieve a better classification result, parameters of CSP and SVM were trained in the offline experiment. In the subsequent online experiment, the results exhibited accuracies of 85.33%, 84%, 72.67% and 81.33%. It indicates that subjects can complete the task fluently and the control system can decode EEG signals with a high recognition rate. Further, the combination in decision table obviously reduces the probability of wrong actions.
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/11878]
专题	深圳先进技术研究院_集成所
作者单位	2017
推荐引用方式 GB/T 7714	Zhouyang Wang,Can Wang,Xinyu Wu,et al. A Control System of Lower Limb Exoskeleton Robots Based on Motor Imagery[C]. 见:. 中国澳门.

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