الفهرس 
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Abstract
Abstract Electroencephalograph (EEG) is an important diagnosis tool in the field of brain wave analysis. The EEG is a continuous recording of Brain waves with varying frequency and amplitude. This work includes study of the brain structure, brain regions, and the techniques of recording brain waves. There are several techniques for monitoring electrical activity of brain showing the important of EEG signals in diagnoses and function control operation, also to study the artifacts that affect the brain signals, Moreover a computer program is used to design a filter to remove the artifacts from the signals, and study the sensors types used for recording brain waves, also study systems used for Brain Computer Interface BCI. This work also deals on a smart measuring setup for brain signal recording and diagnoses and focus on feature extraction and classification using neural network and statistical techniques and design of an interface between the computer and external device. Techniques to monitor brain activity and brain structure and properties of EEG are introduced. Brain Computer Interfaces (BCIs) are divided into two main approaches: the EEG pattern recognition approach based on different mental tasks and the operant conditioning approach based on the self-regulation of the EEG response. Filtering of EEG signal to remove noise or artifacts from the brain signal is introduced using MATLAB and filter lab software. Introduction to sensors used for recording the EEG signals. Introduction to different type of BCI used then present a proposed design for more reliable and faster BCI. Feature extraction methods and classification using neural network techniques and statistical methods. EEG data recorded, training time and number of iteration is recorded for different feature methods. Also using statistical methods for classification. Interface design is made using microcontroller to get control signal or to display the case or diseases type using external display. MATLAB program is used for classification using neural network and statistical techniques.