Optimization of PTSD disorder detection based on nonlinear dynamic analysis of electroencephalogram signals

Objective: Post-traumatic stress disorder (PTSD) is an emotional disorder. This paper aimed to examine the entropy values in patients with PTSD disorder. Methods: The entropy values of 31 EEG channels of 12 subjects (six healthy subjects and six patients with PTSD disorder) with two entropy methods (sample entropy and fuzzy entropy) were calculated. Results: The sample entropy of channels FP1, FP2 and FC6 and fuzzy entropy of channel FC6 were increased in PTSD group and had the highest difference in compare to healthy group. In addition, sample entropy method showed superiority in compare to fuzzy entropy for PTSD recognition problems. Conclusion: Compared to normal group, patients with PTSD disorder were found to have average increased entropy values. Results showed that EEG signals of subjects with PTSD disorder had higher irregularity due to entropy increments. This entropy increment is more obvious in frontal lobe of the brain which related to emotional experiences.