## 2 Materials and Methods
### Experimental Setup  
For the acquisition of EEG signals, we used a BCI system produced by G-Tec and the software applications were developed by us. The data were recorded using eight non-invasive electrodes placed on the scalp according to the international standard 10-20. The channels chosen for electrode placement were: CP3, CP4, P3, C3, Pz, C4, P4 and Cz (Figure 2). These channels were chosen in both hemispheres, according to the appearance of sensorimotor rhythms in these areas. The reference electrode is placed on the right ear. In the first phase, the distance between the ion and the nation is measured, and the ground electrode, which is placed on the FP1 channel, must be located at 10% of the measured distance. Then the electrodes are fixed on the helmet and the skin is contacted with a conductive gel. After completing these steps, the data can be recorded, but not before informing the subject about the tasks he/she has to perform during paradigm. The recordings were made on 60 subjects in the biomedical signal processing laboratory within the faculty of transports, electronics and telecommunications department. Subjects are placed in front of a monitor on which either left and right arrows are displayed successively or nothing is displayed. They must look carefully at the direction indicated by the arrow and imagine the movement of the hand indicated by it and, when nothing appears on the monitor, the subject must relax. The sampling frequency was 1 kHz and the visual stimulus time was 4 s. First, we processed the data obtained so that they could be used in subsequent experiments and analyses, and so that the signals corresponding to the motor imagery movement of the left hand and the right hand, and those corresponding to relaxation were extracted, then the 30 attempts were mediated. Figure 1: The block diagram of BCI system for MI classification. Experimental Design and Protocol  
An important aspect of BCI systems is that the user has to perform various mental tasks and strategies in order to generate specific traits. Brain-computer communication is based on these mental strategies, which are defined and limited by the abilities of the subjects. In other words, BCI systems are created according to the needs and skills of the subjects. However, the subjects also have the duty to learn different strategies and to train their brain to generate certain models that the systems can \"understand\". The most used mental strategies are motor imagery and selection (focusing on different objects, focusing on attention). In paradigms based on the method of selective attention, external stimuli are used in various forms: visual, auditory or somatosensory. The most used stimuli are the visual ones. Paradigms developed based on visual stimuli are divided into two categories depending on the brain characteristics they produce: paradigms based on the P300 potential, paradigms based on SSVEP (Steady State Visual Evoked Potential). Paradigms based on sensorimotor rhythms have a completely different approach. Compared to selective attention-based BCI systems, there is no need to use external stimuli. The movement of any limb or the simple contraction of a muscle is felt in the electrical activity of the brain. Any movement is the result of a brain-generated impulse, not the other way around. Thus, we can say that the movements exist only due to the central nervous system, and the lack of movements is not necessarily due to brain inactivity but to the interruption of the transmission pathway (peripheral nervous system) of the impulse. We can say that there is brain activity related to the movement itself even before it occurs, there being obvious changes in sensorimotor rhythms. These sensorimotor rhythms (SMR) refer to the oscillations that occur in activity in the motor or somatosensory regions of the brain. Just imagining the movement of some limbs can cause changes in sensorimotor rhythms. For classification we need two types of records: records made in the learning paradigm and records made during testing.