Eeg Analysis In Cognitive Function Research

Electroencephalogram (EEG) contains a large number of physiological and pathological information. It can be measured directly on human's body and is suitable for clinical application, can provide diagnostic evidence for some brain diseases, even can be used to treat certain brain diseases. Recently, research on cognitive function has got more and more attention. Effective analysis and evaluation to cognitive function have great significance on detection and treatment of cognitive disorder disease.The paper in the basis of EEG amplifier hardware, using Visual C++ 6.0 to compile the corresponding EEG acquisition software, constitute the signal acquisition module of the detection of cognitive EEG testing and analysis platform, display the EEG with the waveform in real time, and store the data with a separate document to facilitate subsequent analysis and processing. And for cognitive function, design cognitive EEG test to reflect the different states of brain function and collect the EEG under the state of quiet and eyes closed, quiet and eyes opened, calculation test, directive force test and visual spatial tests.Based on the study of classical EEG analysis, use software filtering technology to analyze and process the EEG,Provides a zero-phase digital filter,Independent Component Analysis,Wavelet Transform and other EEG analysis method to pre-treatment the collected EEG to remove noise and interference, and gets the signal power spectral to give a reference cognitive analysis of EEG. Coherence detection methods is used to extract the 40Hz EEG signal reflecting the wake level of concentration of paroxysmal in the process of advanced information processing, it can provide the basis of cognitive status for the selected EEG data segment.Strong nonlinearity is a prominent characteristic of the nervous system. EEG is a chaotic signal with wide range of nonlinear dynamic characteristics, and nonlinear analysis of EEG can provide the changing track of the brain cognitive activities. In this paper, EEG was analyzed by nonlinear dynamics method, and the fractional dimension and approximate entropy of EEG was quickly and efficiently extracted to describe the brain cognitive functions and explore their relationship with cognitive function, and then used as an evaluation index of cognitive function.In the paper, fractal dimensions and approximate entropies of EEG data in different states was calculated. The results indicates that the value of these two parameters in the quiet state with eyes closed are less than that are in the calculation test thinking state, and the value in the quiet state with eyes open are less than that are in the sight-space test state. That means the value of fractal dimensions and approximate entropies in thinking state are greater than that are in quiet state. Analysis of kinetic parameters in different thinking process can help to get guidance parameters in cognitive state, which is of great value to related research and clinical applications.