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EEG topography recognition by neural networks

机译:神经网络的脑电地形识别

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Electroencephalography (EEG) pattern-recognition studies were carried out using EEG topography (readiness potential, or RP, spatiotemporal patterns) generated the moment before voluntary movements of muscles. RPs generated prior to pronouncing syllables and controlling a joystick were studied by experiments and simulation. The spatiotemporal patterns of RPs were measured by multichannel surface electrodes pasted on the subject's scalp. Backpropagation neural networks were used for RP pattern recognition. The results show that RPs generated prior to syllable pronouncement contain some information about those syllables, and that RPs generated prior to joy stick movements contain information on the direction of intended movement. They also show that neural networks can be used to recognize EEG information and so create a new type of man-machine interface for data input.
机译:脑电图(EEG)模式识别研究是使用在肌肉自愿运动之前产生的EEG地形图(准备势或RP,时空模式)进行的。通过实验和仿真研究了在音节发音和控制操纵杆之前生成的RP。通过粘贴在对象头皮上的多通道表面电极来测量RP的时空模式。反向传播神经网络用于RP模式识别。结果表明,在音节发音之前生成的RP包含有关这些音节的一些信息,并且在操纵杆运动之前生成的RP包含有关预期运动方向的信息。他们还表明,神经网络可用于识别EEG信息,从而创建一种新型的人机界面进行数据输入。

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