Abstarct: Surface potential changes on the scalp are measured by arrays of electrodes. EEG signals are the electrical activities of the brain. These signals are primarily used in medical diagnostics and brain function detection. One of these uses is the diagnosis of medical conditions and some psychological problems. It can also be useful in physically disabled patients who have lost their ability to see, move, and control part or all of their bodies. Another use of BCI, which has become more important today, and research on it, is reading the mind. Efforts are in this direction to extract the data from the brain signals and use it in passing through the terms of imaginary password, and so on. This thesis attempts to investigate whether reading the mind using surface electrodes is possible or not, taking a small step in this fascinating path. Therefore, recognition of digits as the subject of this research was selected. In this thesis, the goal is to detect the digits from zero to nine using the EEG signal. Due to the lack of suitable databaxses for Persian digits, as well as the special importance of the databaxse for research, it was decided to create a suitable databaxse. The databaxse was compiled from 13 volunteers, which three videos are shown to each volunteers. These videos include digits from zero to nine in numerical order with BNazanin font in black. The ordering of the digits is random and is displayed after displaying each digit on the whiteboard. The difference between these videos is in the order of the figures. To extract the characteristics of the collected data, the LDA, PSD and DWT methods were used and the SVM classification was used to classify the data. The results obtained from the experiments show that, although using surface electrodes and feature extraction methods, the specified percentages can be found to be acceptable percentages, but these methods are insufficient to achieve a high recognition rate.