# Mental Workload Assessment Using Machine Learning Techniques Based on EEG and Eye Tracking Data
## 4 Results and Discussion  
### Statistical Results  
The investigation aimed to determine whether there was a correlation between eye tracking variables and NASA-TLX scores and task difficulty levels. The analysis revealed that the number and total duration of blinks, the number and total duration of saccades, and the mean of the left and right pupil diameter had the highest correlation with the task difficulty level (rho > 0.1, \(p\) < 0.01). Similarly, the number and total duration of blinks; the mean, maximum value, and standard deviation of saccade amplitude; and the number and total duration of saccades were found to be the variables most correlated with the weighted NASA-TLX score (rho > 0.1, \(p\) < 0.01). All variables, except for fixation duration, exhibited a positive correlation with mental workload. Furthermore, the Kruskal-Wallis (K-W) test demonstrated significant differences in all eye tracking variables based on task difficulty levels. Figure 5 presents graphs illustrating the changes in the mean values of blink, saccade, and pupil-related variables in relation to the difficulty level.  
Figure 5: Change in eye tracking variables according to difficulty level.  
The Spearman correlation test yielded results indicating that the EEG variables associated with theta power from the AF3, AF4, F7, F8, and FC5 channels exhibited the strongest correlation with the level of task difficulty (rho > 0.3, \(p\) < 0.01). These findings demonstrate that as the task difficulty increased, theta power in the prefrontal, frontal, and frontal central regions also increased. Additionally, the correlation coefficients for variables related to theta/alpha power ratios were slightly higher in these same brain regions. Furthermore, it was observed that the level of task difficulty had a negative correlation with the alpha power measured in the O1, O2, T7, and P7 channels, while it had a positive correlation with the alpha power measured in the F7 and F8 channels. Specifically, as the task difficulty increased, the alpha power in the frontal regions increased, whereas the alpha power in the temporal, parietal, and occipital regions decreased.  
The decrease in low beta power is a noticeable trend across various brain regions as the task difficulty increases. A significant correlation was found between the weighted NASA-TLX total score and 75 EEG variables, with a confidence level of 99%. The EEG variables that exhibited the strongest correlation with the weighted NASA-TLX total score were theta power from AF4 and F8, as well as theta/alpha power from AF3, AF4, and F8 (correlation coefficient > 0.3, \(p\) < 0.01). Essentially, as the perceived mental workload intensified, there was an increase in prefrontal and frontal theta power. Conversely, as the perceived workload increases, there is a decrease in low beta power in the prefrontal, frontal, parietal, and occipital brain regions (rho > 0.2, \(p\) < 0.01). The K-W test was employed to assess whether there were significant differences in EEG variables across different difficulty levels. The results revealed that there were indeed differences in difficulty levels at a confidence level of 99% for 49 EEG variables. Upon examining the rank values of these variables, it was observed that 34 out of the 49 variables exhibited a smooth increase or decrease in accordance with the change in task difficulty. This suggests that these variables may play a role in decomposing mental workload into four levels. In more challenging task conditions (2-back and 3-back), the prefrontal, frontal, and central regions displayed higher theta power, while the temporal, parietal, and occipital regions exhibited lower alpha power. Additionally, beta power was lower in almost all brain regions.