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下肢外骨骼机器人控制的脑电感知方法研究
引用本文:王海莲,张小栋,李锴阳,李华聪. 下肢外骨骼机器人控制的脑电感知方法研究[J]. 应用声学, 2016, 24(6): 95-97, 109
作者姓名:王海莲  张小栋  李锴阳  李华聪
作者单位:西北工业大学动力与能源学院,西安交通大学机械工程学院,西北工业大学动力与能源学院,西北工业大学动力与能源学院
基金项目:国家高技术研究发展计划(863计划);国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:将外骨骼机器人技术与BCI系统结合起来,使人体具有了外骨骼机器人的一系列优良特性,同时使外骨骼机器人具备了人体的智能。首先,对外骨骼机器人技术与BCI技术的融合进行了可行性分析,说明了该方法的可行性。其次,通过实验采集了六种想象运动的脑电信号,选取了C3、C4通道的脑电信号,并对其进行了去噪处理。然后,对经过预处理的六种想象运动的脑电信号通过小波变换进行了分解,提取了包括小波分解系数和能量系数的脑电信号小波特征。最后,针对所提取的小波特征,采用了最小二乘支持向量机对这六种想象运动模式进行分类处理。

关 键 词:外骨骼机器人  EEG  小波变换  最小二乘支持向量机
收稿时间:2015-11-30
修稿时间:2016-01-08

EEG sensing method study for lower extremity exoskeleton robot control
Wang Hailian,Zhang Xiaodong,Li Kaiyang and Li Huacong. EEG sensing method study for lower extremity exoskeleton robot control[J]. Applied Acoustics(China), 2016, 24(6): 95-97, 109
Authors:Wang Hailian  Zhang Xiaodong  Li Kaiyang  Li Huacong
Abstract:Combing the exoskeleton robotics with the BCI system can make the human body not only has series of excellent features of the exoskeleton robot, but also the exoskeleton robot can have human intelligence. First of all, the feasibility of the exoskeleton robot technology integrates with the BCI technology was analyzed. Secondly, six motion patterns of EEG method which was used for the control of exoskeleton robot were conducted and the EEG signals of six kinds of imagined movement were collected in the experiment; C3 and C4 channels of EEG signals were selected. Thirdly, the signals which have been pre processed via Wavelet transform were decomposed, and the wavelet coefficients and energy coefficients for the feature extraction were extracted. Finally, the method of LS-SVM was used to classify and output the six imagined movement patterns.
Keywords:lower extremity exoskeleton robot   EEG    wavelet transformation   LS-SVM
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