Processing Of The EEG And Its Application In The Artificial Hands

The artificial hands based on EEG is the system for controlling or communicating with other electronic devices by human intentions. It is the important branch of the Biomedical Engineering. The research deals with the neurophysiology, rehabilitation engineering, signal process technology and so on. The electroencephalograph(EEG) feature extraction and EEG classification play important roles.So far, the studies in EEG have been concentrated on providing an efficient way to communicate with the outer-world and recall some limb functions for individuals with severe motor defects. In the research of artificial hands controlled by EEG, finding that the EEG identification correctly plays the key role in the artificial hands system. EEG is very complicated biologic signal. The EEG collected directly isn't of enough information and can't adapt to the development of artificial hand. So it is very important to choose correct methods of EEG feature extraction and classification. For improving the precision of motion, a kind of control model is devised based on wavelet packet transformation and BP algorithm after summing up and studying other works in this field in this paper.First, study EEG deeply and other works in this field. By these preparative, the author analyses the feasibility of control artificial with EEG and devises a control model controlling artificial hand with mental tasks EEG.Second, research on wavelet transformation theory and filter noises from EEG using it. Furthermore, research on wavelet packet transformation. Multiresolution analysis theory is used to extract different rhythm power features which represent the corresponding EEG based on EEG rhythm.Third, the structure of BP neural network(NN) is studied and also improved. Parameters of NN are set correctly. The different EEG is classified by devised NN which is self-adjusting and self-learning. Control command is outputted after classification by NN.Finally, a simple artificial hands motion experiment is done using the knowledge of digital and simulation circuit. Finish the serial communication from PCs to outer control circuit on the development environment LabVIEW and design a brain-computer interface of EEG displaying which can do the simple EEG processing.