An Approach for Measurement and Recognition of Electroencephalography

With the fast development of brain computer interface (simply called BCI), electroencephalography (simply called EEG) will be another interesting bio-electrical signal applied in the dexterous control of the robot hand after EMG. In order to realize it finally, pattern recognition of human hand activities based on EEG is a very important and elementary research objective. After discussing the signal features of EEG, a two-channel measuring system about EEG signal is at first set up in this paper. And then, an artificial neural network classifier is presented based on the five spectral features of EEG. After sample learning is over, the artificial neural network can output good results of pattern recognition about human hand activities according to input spectral features of these mental tasks.