The proposed system comprises of three main parts, the first one being the wireless acquisition module, second is the signal processing module and the third, the last one is the output hardware module in which the user inputs get implemented as the final desired outputs. The following Fig. 4.1 shows the overall block diagram of the system implemented in our work. The workflow can be mainly classified into two parts. The first part is the electroencephalogram (EEG) acquisition and signal processing in real time. As shown in Fig. 4.1 next, the left side of the block diagram covers the first part of our work that is data acquisition, signal processing, and implementation of this processed data into real-time robot commands. The data that is referred to include only the raw EEG data provided by various electrodes in the EMOTIV EPOC neuroheadset. The second part of our work is acquisition, processing, and implementation of the gyroscope signals. Here, the gyroscope that is referred to is embedded in the EMOTIV EPOC neuroheadset. This has been mentioned on the right-hand side of the block diagram which can also be named as the mouse emulator part, that is, the data from the gyroscope is used to drive the mouse pointer on the computer to access the GUI in MATLAB. The third part is the design of GUI in MATLAB, shown in the right, bottom corner of the block diagram, which is to be concentrated upon by the user. When the abovementioned sections work at the same time simultaneously, the user can access his GUI in MATLAB to communicate with the Arduino-based autonomous navigation robot in real time.
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