title: Automatic detection of a phases of the cyclic alternating pattern during sleep.
abstract: This study aimed to develop an automatic algorithm to detect the activation phases (A phases) of the Cyclic Alternating Pattern. The sleep EEG microstructure of 4 adult, healthy subjects was scored by a sleep medicine expert. Features were calculated from each of the six EEG bands (low delta, high delta, theta, alpha, sigma and beta), and three additional characteristics were computed: the Hjorth activity in the low delta and high delta bands, and the differential variance of the raw EEG signal. The correlation between couples of features was analyzed to find redundancies for the automatic analysis. The features were used to train an Artificial Neural Network to automatically find the A phases of CAP. The data were divided into training, validation and testing set, and the visual scoring provided by the clinician was used as the desired output. The statistics on the second by second classification show an average sensitivity equal to 76%, specificity equal to 83% and accuracy equal to 82%. The results obtained are encouraging, since an automatic classification of the A phases could benefit the practice in clinics, preventing the physician from the time-consuming activity of visually scoring the sleep microstructure over the whole eight-hour sleep recordings. Moreover, it would provide an objective criterion capable of overcoming the problems of inter-scorer variability.
authors.affiliation: Politecnico di Milano, Dept. of Biomedical Engineering, P.zza Leonardo da Vinci 32, 20133, Milan, Italy. saral.mariani@mail.polimi.it
authors.forename: Sara
authors.initials: S
authors.lastname: Mariani
authors.forename: Anna M
authors.initials: AM
authors.lastname: Bianchi
authors.forename: Elena
authors.initials: E
authors.lastname: Manfredini
authors.forename: Valentina
authors.initials: V
authors.lastname: Rosso
authors.forename: Martin O
authors.initials: MO
authors.lastname: Mendez
authors.forename: Liborio
authors.initials: L
authors.lastname: Parrino
authors.forename: Matteo
authors.initials: M
authors.lastname: Matteucci
authors.forename: Andrea
authors.initials: A
authors.lastname: Grassi
authors.forename: Sergio
authors.initials: S
authors.lastname: Cerutti
authors.forename: Mario G
authors.initials: MG
authors.lastname: Terzano
mesh_terms: D000328:Adult; D001331:Automation / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D016571:Neural Networks, Computer; D012894:Sleep Stages / Q000502:physiology*