Assessment of the EEG complexity during activations from sleep

Authors:
I. Chouvarda;V. Rosso;M. O. Mendez;A. M. Bianchi;L. Parrino;A. Grassi;M. Terzano;S. Cerutti
Affiliations:
Lab of Medical Informatics, The Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece and Biomedical Engineering Department, Politecnico di Milano, Italy;Sleep Disorders Centre, Department of Neurology, University of Parma, Parma, Italy;Facultad de Ciencias, Diagonal Sur S/N, Zona Universitaria, San Luis Potosi, S.L.P., Mexico;Biomedical Engineering Department, Politecnico di Milano, Italy;Sleep Disorders Centre, Department of Neurology, University of Parma, Parma, Italy;Sleep Disorders Centre, Department of Neurology, University of Parma, Parma, Italy;Sleep Disorders Centre, Department of Neurology, University of Parma, Parma, Italy;Biomedical Engineering Department, Politecnico di Milano, Italy
Venue:
Computer Methods and Programs in Biomedicine
Year:
2011

Citing 4
Cited 1

Approach to an irregular time series on the basis of the fractal theory

Physica D
Fractal dimension characterizes seizure onset in epileptic patients

ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04
Discrimination ability of individual measures used in sleep stages classification

Artificial Intelligence in Medicine
Non-linear analysis of EEG signals at various sleep stages

Computer Methods and Programs in Biomedicine

Automatic classification of sleep stages based on the time-frequency image of EEG signals

Computer Methods and Programs in Biomedicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

The present study quantitatively analyzes the EEG characteristics during activations (Act) that occur during NREM sleep, and constitute elements of sleep microstructure (i.e. the Cyclic Alternating Pattern). The fractal dimension (FD) and the sample entropy (SampEn) measures were used to study the different sleep stages and the Act that build up the sleep structure. Polysomnographic recordings from 10 good sleepers were analyzed. The complexity indexes of the Act were compared with the non-activation (NAct) periods during non-REM sleep. In addition, complexity measures among the different Act subtypes (A1, A2 and A3) were analyzed. A3 presented a quite similar complexity independently of the sleep stage, while A1 and A2 showed higher complexity in light sleep than during deep sleep. The current results suggest that Act present a hierarchic complexity between subtypes A3 (higher), A2 (intermediate) and A1 (lower) in all sleep stages.