## 4 Results and Discussion  
There are six health controls and six PTSD cases. In each subject, the data of 31 channels is presented as a time-series dataset with a size of 31 \(\times\) 50,000. After applying k-means (k = 6) we applied individual SVM models to obtain 31 value weights showing, respectively, the importance of 31 channels in classifying six clusters of 12 subjects. With the same combination of k-means and SVM, we generate the fixed matrix of weights (size 12 \(\times\) 31 for 31 channels in 12 data subjects). To compute the importance of each channel for differentiating healthy subjects and PTSD subjects, we compare the different weights of each channel over 12 data subjects by 31-line graphs, matching, respectively, 31 channels. When we compare these 31-line graphs, we define a common pattern in three channels, F4, F8, and Pz. In these three channels, more than 90% of the weights in healthy controls are higher than in PTSD cases (Figure 3). This may imply a significant difference between the two groups of subjects, healthy and PTSD, which needs to be checked by hypothesis testing. The weights of channel 4 (channel F4), channel 12 (channel F8), and channel 19 (channel Pz) are significantly higher in the healthy control group (H) versus the PTSD group (P) (Figure 4). All of these channel weights are higher in healthy subjects than in subjects with PTSD except for three values: subject P1 in channel 4 (F4), subject P5 in channel 8 (P4), and subject P3 in channel 19 (Pz). In channel F4, all weights in healthy subjects are equal to or greater than 0.01297, while all of the weights in subjects with PTSD are lower than this value (Figure 3). The pattern is  
Figure 4: Red numbers are minimum weight of each channel. (**a**) Box plot of weights of channel F4 in each group of subjects; (**b**) box plot of weights of channel F8 in each group of subjects; (**c**) box plot of weights of channel Pz in each group of subjects. Figure 3: The weights of channels per subject for the SVM hyperplane that divides channels of subjects into 6 groups. similar in channel F8 and Pz with the different bordering values of 0.019724 in channel F8 and 0.012953 in channel Pz. We test the hypothesis of differences in channel weights between the healthy and PTSD groups using the Mann-Whitney U test (Table 1). The \(p\)-values of the Mann-Whitney U test for channels F4, F8, and Pz are statistically significant for average weights in healthy subjects when compared to average weights in PTSD cases (Table 1). These findings suggest that channels F4, F8, and Pz may differentiate PTSD and healthy controls based on our combination of machine learning-based weights. These results are consistent with previous reports for channels F4 and Pz as important channels to differentiate healthy subjects and subjects with PTSD [12,18]. The study by [PERSON] [19] found F4 and Pz to be channels associated with the disorder [18]. The main function of channel F4 is like channel F3; namely, motor planning for the right arm movement while channel F4 mainly controls motor planning for the left arm [15]. This symmetry explains the similarity in channel F4 and channel F3 in the discriminating between healthy subjects and subjects with PTSD. Previous studies have reported the association of these channels with PTSD in Refs. [12,15]. Our previous Hurst exponent analysis found an association of channel F3 with PTSD. In that paper, we applied the Hurst exponent as a useful statistical method to find the distinctive channel of the brain between subjects with PTSD and healthy people based on long-term memory. Based on that paper, the F3 channel of all six healthy controls was higher than the PTSD cases [1]. In the current paper, we applied machine learning methods to confirm the previous work and find more diagnostic channels. The current study suggests that channels F4, F8, and Pz are important factors in discriminating between healthy subjects and subjects with PTSD. F3 and F4 are parallel channels, and both are related to long-term memory.