NDLI: Analysis of A-phase transitions during the cyclic alternating pattern under normal sleep

Content Provider	Springer Nature Link
Author	Mendez, Martin Oswaldo Chouvarda, Ioanna Alba, Alfonso Bianchi, Anna Maria Grassi, Andrea Arce Santana, Edgar Milioli, Guilia Terza, Mario Giovanni Parri, Liborio
Copyright Year	2015
Abstract	An analysis of the EEG signal during the B-phase and A-phases transitions of the cyclic alternating pattern (CAP) during sleep is presented. CAP is a sleep phenomenon composed by consecutive sequences of A-phases (each A-phase could belong to a possible group A1, A2 or A3) observed during the non-REM sleep. Each A-phase is separated by a B-phase which has the basal frequency of the EEG during a specific sleep stage. The patterns formed by these sequences reflect the sleep instability and consequently help to understand the sleep process. Ten recordings from healthy good sleepers were included in this study. The current study investigates complexity, statistical and frequency signal properties of electroencephalography (EEG) recordings at the transitions: B-phase—A-phase. In addition, classification between the onset–offset of the A-phases and B-phase was carried out with a kNN classifier. The results showed that EEG signal presents significant differences (p < 0.05) between A-phases and B-phase for the standard deviation, energy, sample entropy, Tsallis entropy and frequency band indices. The A-phase onset showed values of energy three times higher than B-phase at all the sleep stages. The statistical analysis of variance shows that more than 80 % of the A-phase onset and offset is significantly different from the B-phase. The classification performance between onset or offset of A-phases and background showed classification values over 80 % for specificity and accuracy and 70 % for sensitivity. Only during the A3-phase, the classification was lower. The results suggest that neural assembles that generate the basal EEG oscillations during sleep present an over-imposed coordination for a few seconds due to the A-phases. The main characteristics for automatic separation between the onset–offset A-phase and the B-phase are the energy at the different frequency bands.
Starting Page	133
Ending Page	148
Page Count	16
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	54
Issue Number	1
e-ISSN	17410444
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-08-08
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Sleep CAP Nonlinear analysis Border identification EEG Human Physiology Biomedical Engineering Imaging Radiology Computer Applications
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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