Migraine detection through spontaneous EEG analysis.
Spontaneous EEG patterns are studied to detect migraine patients both during the attack and in headache-free periods. The EEG signals are analyzed through the wavelets and both scale-dependent and scale-independent features are computed to characterize the patterns. The classification is carried out by a supervised neural network. The efficiency of the method is evaluated through the Receiver Operating Characteristic (ROC) analysis and the Wilcoxon-Mann-Whitney (WMW) test. Although a high discrimination is observed with one single neural output, a complete separation among MwA patients and healthy subjects is obtained when a scatter plot is drawn in the plane of two suitable neural outputs.
Bellotti
R
R
Dipartimento di Fisica, Università di Bari, Italy.
De Carlo
F
F
de Tommaso
M
M
Lucente
M
M
D000293:Adolescent; D000328:Adult; D000368:Aged; D001921:Brain / Q000473:pathology*; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008881:Migraine Disorders / Q000175:diagnosis* / Q000473:pathology*; D008959:Models, Neurological; D009415:Nerve Net; D009474:Neurons / Q000473:pathology; D012372:ROC Curve