title: Automatic detection of CAP on central and fronto-central EEG leads via Support Vector Machines.
abstract: The aim of this study is to implement a high-accuracy automatic detector of the Cyclic Alternating Pattern (CAP) during sleep. EEG data from four healthy subjects were used. Both the C4-A1 and the F4-C4 leads were analyzed for this study. Seven features were extracted from each of the two leads and two separate studies were performed for each set of descriptors. For both sets, a Support Vector Machine was trained and tested on the data with the Leave One Out cross-validation method. The two final classifications obtained on the two sets were merged, by considering a CAP A phase scored only if it had been recognized both on the central and on the frontal lead. The length of the A phase was then determined by the result on the fronto-central lead. This method leads to encouraging results, with a classification sensitivity on the whole dataset equal to 73.82%, specificity equal to 85.93%, accuracy equal to 84,05% and Cohen's kappa equal to 0.50.
authors.affiliation: Politecnico di Milano, Dept of Biomedical Engineering, P.zza Leonardo da Vinci 32, 20133 Milan, Italy. sara1.mariani@mail.polimi.it
authors.forename: Sara
authors.initials: S
authors.lastname: Mariani
authors.forename: Andrea
authors.initials: A
authors.lastname: Grassi
authors.forename: Martin O
authors.initials: MO
authors.lastname: Mendez
authors.forename: Liborio
authors.initials: L
authors.lastname: Parrino
authors.forename: Mario G
authors.initials: MG
authors.lastname: Terzano
authors.forename: Anna M
authors.initials: AM
authors.lastname: Bianchi
mesh_terms: D000204:Activity Cycles / Q000502:physiology*; D000328:Adult; D000465:Algorithms; D001683:Biological Clocks / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D060388:Support Vector Machine