Segmentation of sleep EEG signal by optimal thresholds

Proceedings of the 9th IASTED International Conference on Biomedical Engineering, BioMed 2012

Volumn , Issue , 2012, Pages 114-121

  Migotina, Daria ^a   Rosa, Agostinho ^a  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

Biomedical signal processing; Image processing and signal processing; Medical imaging

Indexed keywords

AGE GROUPS; BIOMEDICAL SIGNAL PROCESSING; CLINICAL ANALYSIS; EEG SIGNALS; FREQUENCY CHARACTERISTIC; MICRO-STRUCTURAL; OPTIMAL THRESHOLD; SEGMENTATION PROCEDURE; SLEEP EEG; SLEEP ELECTROENCEPHALOGRAM; SPECTRAL CHARACTERISTICS; THRESHOLD CRITERION; THRESHOLDING; UNIVERSAL RELATIONSHIP;

BIOMEDICAL ENGINEERING; IMAGE PROCESSING; MEDICAL IMAGING; OPTIMIZATION; SLEEP RESEARCH;

ELECTROENCEPHALOGRAPHY;

EID: 84863713559     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2316/P.2012.764-063     Document Type: Conference Paper

References (16)

1. A. Gevins and A. Rémond, Handbook of Electroencephalography and Slinical Neurophysiology, Vol. I: Methods of Analysis of Brain Electrical and Magnetic Signals. Elseiver, Amsterdam, 1987.
2. G. Pfurtscheller, F.H. Lopes da Silva, Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin. Neurophysiol., vol. 110, no. 11, pp.184257, 1999.
3. M.G. Terzano, L. Parrino, A. Smerieri et al., Altas, rules, and recording techniques for the scoring of cyclic alternating pattern (CAP) in human sleep. Sleep Medicine, vol. 2, 537-553, 2001.
4. M.G. Terzano, L. Parrino, G.F. Mennuni, Phasic Events And Microstructure Of Sleep. Martano Editore Lecce, 1997.
5. E-Medicine URL: http://www.emedicine.com.
6. G. Bodenstein and H.M. Praetorius, Feature Extraction from the Electroencephalogram by Adaptive Segmentation. Proc. of the IEEE, vol. 65, no. 5, May 1977.
7. R. Agarwal and J. Gotman, Adaptive Segmentation of Electroencephalographic Data Using a Nonlinear Energy Operator. Proc. IEEE International Symposium on Circuits and Systems (ISCAS'99), vol. 4, 199-202, 1999.
8. H. Hassanpour and M. Shahiri, Adaptive Segmentation Using Wavelet Transform. IEEE International Conference on Electrical Engineering (ICEE), Lahore, Pakistan, 2007.
9. Hassanpour, H., Anisheh, S.M., Adaptive Segmentation using Fractal Dimension and Wavelet Transform. IEEE Int. Workshop on Signal Processing and its App., Sharjah, U.A.E., (2008).
10. A. Kaplan, J. Roschke, B. Darkhovsky, J. Fell, Macrostructural EEG characterization based on nonparametric change point segmentation: application to sleep analysis. J Neurosci Methods, vol. 106, no. 1, 81-90, 2001.
11. B.E. Brodsky, B.S. Darkhovsky, A.Ya. Kaplan, S.L. Shishkin, Nonparametric method for the segmentation of the EEG. Computer Methods and Programs in Biomed., vol. 60, no. 2, 93-106, 1999.
12. Z. Jane Wang, P. Wen-Hsin Lee, M.J. McKeown, A novel segmentation, mutual information network frame work for EEG analysis of motor tasks. Biomed Eng Online, vol. 8, no. 5, 2009.
13. WWW:http://www.mathwave.com/
14. M.H. DeGroot, Probability and Statistics, 3rd edition. Addison-Wesley, 1991.
15. A.M. Law and W.D. Lelton, Simulation Modeling and Analysis (Third Edition). McGraw Hill, 2000.
16. Herrera L.J., Fernandes C.F., Mora A.M., Migotina D., Rosa A.C. and Merelo J.J., Symbolic Representation of EEG for Sleeping Stage Classification. Proc. ISDA'11, Cordoba, Spain, pp. 253-258.