title: Permutation entropy to detect vigilance changes and preictal states from scalp EEG in epileptic patients. A preliminary study.
abstract: Permutation entropy (PE) was recently introduced as a very fast and robust algorithm to detect dynamic complexity changes in time series. It was also suggested as a useful screening algorithm for epileptic events in EEG data. In the present work, we tested its efficacy on scalp EEG data recorded from three epileptic patients. With a receiver operating characteristics (ROC) analysis, we evaluated the separability of amplitude distributions of PE resulting from preictal and interictal phases. Moreover, the dependency of PE on vigilance state was tested by correlation coefficients. A good separability of interictal and preictal phase was found, nevertheless PE was shown to be sensitive to changes in vigilance state. The changes of PE during the preictal phase and at seizure onset coincided with changes in vigilance state, restricting its possible use for seizure prediction on scalp EEG; this finding however suggests its possible usefulness for an automated classification of vigilance states.
authors: Department of Psychology, University of Bologna, Viale Carlo Berti Pichat 5, 40100 Bologna, Italy. angela.bruzzo@libero.it
authors: Angela A
authors: AA
authors: Bruzzo
authors: Benno
authors: B
authors: Gesierich
authors: Maurizio
authors: M
authors: Santi
authors: Carlo Alberto
authors: CA
authors: Tassinari
authors: Niels
authors: N
authors: Birbaumer
authors: Guido
authors: G
authors: Rubboli
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001921:Brain / Q000503:physiopathology*; D004569:Electroencephalography; D019277:Entropy; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012640:Seizures / Q000145:classification*