Extracting brain behavior change in patients with migraine by quantitative analysis of electroencephalogram signal of patients compared to healthy people

چکیده مقاله

Background: Migraine disease is the second most common cause of headaches. Despite the high prevalence, the exact etiology of migraine is yet unknown. In this study, to evaluate the behavior change of electroencephalography (EEG) signals in migraine patients, various features of the EEG signals of migraine patients and healthy controls (HCs) were extracted and compared.

Methods. This cross-sectional analytical study was conducted on 21 HCs and 18 migraine patients. Various features, such as fractal dimension (FD), approximate entropy (ApEn), and largest Lyapunov exponent (LLE), were calculated from the EEG signals of migraine patients and HCs. Then different frequency sub-bands of delta, theta, alpha, beta, and gamma were extracted using the wavelet transform, and the energy of these sub-bands was computed. By calculating the mean and variance of the features and applying statistical tests, the feature changes were compared between two groups, and channels with significant differences were identified. Results. The mean of ApEn, FD and energy of all frequency sub-bands in most of the analyzed channels was higher in migraine patients than in HCs. The mean LLE was mostly lower in migraine patients than in healthy controls. According to the statistical tests, the energy of theta and delta frequency sub-bands with 36 and 35 channels was the feature with the highest number of channels, with a significant difference. In this study, P values less than 0.05 were considered statistically significant. Conclusion. Migraine patients may have a less sophisticated brain dynamic system due to an increase in irregularity and randomness …