*2.3.1 Test dataset acquisition and observation*

The test is being conducted in an anechoic chamber as we can observe at the background of the subjects in Table, in order to minimize the external noise and to isolate the experiment. The subject's voluntary consent has been taken prior for performing this particular test experiment. Also, the subjects are strictly advised to be in a relaxed mental condition for 10 minutes before the test perusal and before 30 seconds of the performance of the test, the subject's eye movements (closed state and opened state) also analyzed by the EmotivPro application in order to remove the eye blink artifacts. All subjects have performed the test successfully as instructed.

As the subject's experiments begin, their mental state is being captured in the camera and the state at which the subjects are present is being noted and presented in the mental state column of **Table 1**. After ensuring the optimum contact quality, the EEG data following common reference montage is analyzed in the live, with EmotivPro license, it is possible to record the current EEG data of its respective electrodes.


#### **Table 1.**

*The table displays the specific subject with their respective mental task.*

After performing the tests on the subjects, the raw EEG data which is recorded during experimentation is stored in the EmotivPro application cloud. This recorded data is exported to the client server system in the .csv format, **Figure 3** these files can be assessed through the links provided in the above **Table 1** for the respective subject test.


#### **Figure 3.**

*The imported data in the workplace.*


#### **Figure 4.**

*The subject's EEG data in the work space.*

This .csv file contains the recorded potentials of all 5 channels (AF3, AF4, T7, T8, Pz) at their respective timestamp. This data is copied and imported into the workspace of MATLAB. Database toolbox is used to read, write, import and export the data of .csv files **Figure 4**. Digital signal processing toolbox is used for converting time domain signal to frequency domain signal.

The main principle of fast Fourier transform is it converts the time domain signal into frequency domain signal. As the raw data is injected into the FFT in matlab, it analyzes the frequencies of the time domain signals. The xfft vs. absolute part of the FFT gives us the frequency domain signal. In this case, there is a large amount of noise observed in the frequency domain graph for the test dataset. Hence, in order to remove the noise and the high peak which is near to zero, the smoothing filters were applied independently and a band pass filter is also applied between 4 to 45 Hz, as the result of the experiment lies within that particular frequency range.

1.The length of the signal is assigned to variable = nfft,


*Brain Computer Interface Drone DOI: http://dx.doi.org/10.5772/intechopen.97558*

**Table 2.** *This table represents the experimental analysis graphically.*

