## 4 Results and Discussion
### Comparison of Helmets
#### 4.3.2 Power Spectral Density in Alpha Waves
In particular, the Chameleon headset highlights a more pronounced difference between the two states, suggesting greater sensitivity to detect these variations. Figure 41 displays the graphs obtained for Subject 2. As shown in Figure 41, the values obtained for both headsets are within a similar range. For the Ultracortex headset, the average PSD was 10.12 \(\upmu\)V\({}^{2}\)/Hz in the active state and  
Figure 41: Alpha PSD (8 to 13 Hz) of subject 2 (**a**) with the Ultracortex headset, (**b**) with the Chameleon headset. 30.36 \(\mathrm{\upmu V^{2}/Hz}\) in the relaxed state, with a difference of 20.24 \(\mathrm{\upmu V^{2}/Hz}\). However, the Chameleon headset recorded an average of 7.02 \(\mathrm{\upmu V^{2}/Hz}\) in the active state and 32.27 \(\mathrm{\upmu V^{2}/Hz}\) in the relaxed state with a difference of 25.25 \(\mathrm{\upmu V^{2}/Hz}\). These results again highlight a substantial difference between the active and relaxed states of the Chameleon headset, reinforcing its superior ability to discriminate between the two states. For Subject 3, the graphs shown in Figure 42 were obtained. Graphs for Subject 3 indicate that the signals recorded during active and relaxed states were similar. This similarity significantly hindered the ability to distinguish between the two states, which could be due to several factors. One of the primary reasons may be the subject's difficulty in attaining a proper state of relaxation. Figure 42: Alpha PSD (8 to 13 Hz) of subject 3: (**a**) with the Ultracortex headset, (**b**) with the Chameleon headset. Regarding the Ultracortex headset, the average PSD was 6.56 \(\upmu\)V\({}^{2}\)/Hz in the active state and 6.63 \(\upmu\)V\({}^{2}\)/Hz in the relaxed state with a minimal difference of only 0.07 \(\upmu\)V\({}^{2}\)/Hz. This result suggests an almost nonexistent ability to differentiate between the two states. In contrast, when using the proposed headset, the PSD was 30.19 \(\upmu\)V\({}^{2}\)/Hz in the active state and 33.43 \(\upmu\)V\({}^{2}\)/Hz in the relaxed state with a significant difference of 3.24 \(\upmu\)V\({}^{2}\)/Hz. Although this difference is slight, it is more meaningful in terms of the ability to discriminate between the two states than the commercially available headset. In Table 5, the mean PSD values and standard deviations (SDs) for the different subjects are presented for both helmets. Table 5 presents the results obtained from the three subjects, showing their mean PSD values and standard deviations, as well as the total values for each helmet. For example, the mean PSD for the Ultracortex helmet in the active state was 8.19 \(\upmu\)V\({}^{2}\)/Hz, while in the relaxed state, it reached 16.15 \(\upmu\)V\({}^{2}\)/Hz, resulting in a difference of 7.96 \(\upmu\)V\({}^{2}\)/Hz. In contrast, the Chameleon helmet had a total mean PSD of 19.65 \(\upmu\)V\({}^{2}\)/Hz in the active state and 31.77 \(\upmu\)V\({}^{2}\)/Hz in the relaxed state with a difference of 12.12 \(\upmu\)V\({}^{2}\)/Hz. This greater difference confirms the superior ability of the Chameleon helmet to distinguish between both states. This study highlights the importance of alpha waves as an indicator of relaxation in BCI systems. The Chameleon-1 headset demonstrated a superior ability to discriminate between active and relaxed states with alpha waves, showing significant PSD differences in Subjects 1, 2, and 3, validating its effectiveness. Comparison Between Emotive and Chameleon  
In this case, the process was similar to previous experiments but with a shorter recording time of 26 s: 13 s in an active state (eyes open) and 13 s in a relaxed state (eyes closed). Data were collected from the F3 and F4 electrodes at a sampling rate of 128 Hz. The EEG signals were preprocessed using bandpass filtering (0.5-50 Hz) and notch filters at 50 Hz and 60 Hz. Subsequently, the signals were combined into a single unified signal and processed with a fourth-order Butterworth filter (8-13 Hz). Then, a Fourier Transform (FFT) was performed to convert the signal into the frequency domain.