Analysis Of Attention EEG And Realization Of Brain Computer Interface System

With the development of the society,metal work plays a more and more important role in the human social activities.Whether the attention is concentrated directly affects the working efficiency,therefore,it is of great significance to analysis and classify the EEG signals of different attention tasks.This thesis extract the EEG signals that contains low frequency bands,then analysis the signals by DCCA and MF-DCCA.So it can achieve the purpose of accurately determining the brain active attention.The main research contents are the following three points in my thesis.(1)Analysing the attention EEG by DCCA.Calculating the EEG signals of the meditation and daze subjects,then get the different DCCA index.At last,this thesis find that there is a clear difference of the different attention states' DCCA index.When people pay attention to something,the DCCA index will reduce.As a result,Doctors can observe the change of EEG signals' DCCA index,to judge the subjects' concentration levels.It makes important sense to the rehabilitation treatment of brain diseases.(2)Analysing the attention EEG by MF-DCCA.We use another algorithm to study the EEG.The algorithm prove multiple characteristics of EEG signals in different parameter and angle.Finally,This thesis finds that the brain electrical signals in daze state have more multifractal properties than the signals in mediation state.(3)The implantation of brain-machine interface by Android and Java system.In order to make the research has practical significance,this thesis build a brain-machine interface system by using Android mobile intelligent device,the sensor,and Server-side Web applications.The system can realize real-time acquisition,analysis and store the EEG signals,it is important to further study the EEG signals in the future.