Research of brain-computer interface based on PSD and ANN

被引：0
|
作者：
Zhao, Hai-Bin [1 ]
Wang, Hong [1 ]
机构：
[1] School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, China
来源：
Xitong Fangzhen Xuebao / Journal of System Simulation | 2007年 / 19卷 / 19期
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摘要：
The Brain-Computer Interface (BCI) is a communication system that does not depend on the brain's normal output pathways of peripheral nerves and muscles. EEG signals were classified during different mental tasks using Power Spectral Density (PSD) and artificial neural network. The EEG signal was preprocessed and the PSD was computed based on Multiple Signal Classification (MUSIC) algorithm, and the features were extracted from the PSD of 6-13 Hz. Learning Vector Quantization (LVQ) neural network was used to classify two different mental tasks. From the simulation of the experiment, a good result was got, and this method is very quick.
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页码：4581 / 4582
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