EEG Signals Acquiring And Processing & Analysis

A wealth of brain information is provided in EEG signals. We can learn about different cerebral function states by analysing and processing EEG signals Electroencephalogram (EEG) has been widely used in neurophysiology researches and clinical disease diagnosis, because it is safe, painless, economical and convenient. Strong and effective method to analyse and process EEG signals plays an important role in some aspects, for example, estimating on the human mental statements, diagnosing and treating brain and neurological diseases, monitoring the depth of anesthesia, analyzing sleep quality and stages, and so on.We have finish our research work by using the new technologies of electronic, computer, and modern signal processing. The main research work of this dissertation has five parts as follows: First, the basic knowledge on EEG signals is summarized, that is, generation mechanism, data collection and contents in frequency band are stated, the significance of EEG is summed up, and the development status and trend in recent years at home and abroad in this research field are reviewed.。Second, we have study how to use the discrete harmonic wavelet packet transformation to analysis the EEG signals. Discrete harmonic wavelet packet transformation is employed to extract EEG basic rhythms How to acquire quantitative character parameters is illuminated by frequency band energy ratio of all basic rhythms from single electrode (FBER-S) and how to use them in clinical diagnose is discussedThird, the software and hardware of computer controlling and communicating with external device by USB bus are completed. And it runs well.Fourth, we have finished the structure analysis of the EEG monitoring and analysis system's main computer software and the design of its main module. They are real time monitoring module, adjacent area comparing filter module, classic frequency analysis and modern frequency analysis module, wavelet analysis module, and brain electrical activity mapping (BEAM) module. And they have passed test.Fifth, we have studyed the exciting discharged properties of the biological neurons modeled by H-H equations coupled on small-world networks having the mechanism of the side restrain, when the neurons are excited by current under the different conditions of the noise power and coupling intensity, by defining two new measures exciting frequency f main and average exciting intensity p sum The results show that the exciting frequency increases near linearly along with increasing the stimulation; the exciting intensity decrease with the increase the of the stimulation,when the dc stimulation exceeds the stimulating threshold. The influence of the coupling intensity on excitation properties is notable. The stronger the coupling intensity is the lower the exciting frequency is, however, the stronger the coupling intensity is the bigger the exciting intensity is.