Analysis of sleep EEG activity during hypopnoea episodes by least squares support vector machine employing AR coefficients

Expert Systems with Applications

Volumn 37, Issue 6, 2010, Pages 4463-4467

  Übeyli, Elif Derya ^a   Cvetkovic, Dean ^b   Holland, Gerard ^c   Cosic, Irena ^b  

^a TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY   (Turkey)

^b RMIT UNIVERSITY   (Australia)

^c St Luke's Hospital   (Australia)

Author keywords

AR coefficients; Electroencephalogram (EEG); Least squares support vector machines; Sleep apnoea hypopnoea

Indexed keywords

AUTO-REGRESSIVE; AUTOMATIC DETECTION; CLASSIFICATION ACCURACY; EEG SIGNALS; ELECTRICAL ACTIVITIES; HUMAN EEG; HUMAN ELECTROENCEPHALOGRAM; HYPOPNOEA SYNDROME; INPUT PATTERNS; LEAST SQUARES SUPPORT VECTOR MACHINES; OBSTRUCTIVE SLEEP APNOEA; SLEEP EEG; THREE ELECTRODE; TWO STAGE;

ARGON; BRAIN; ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; GEARS; KALMAN FILTERS; MULTILAYER NEURAL NETWORKS; OPTICAL SENSORS; SLEEP RESEARCH; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 77249090169     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.12.065     Document Type: Article

References (27)

1. Adeli H., Zhou Z., and Dadmehr N. Analysis of EEG records in an epileptic patient using wavelet transform. Journal of Neuroscience Methods 123 1 (2003) 69-87
2. Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control, AC-19 (1974) 716-723
3. Cortes C., and Vapnik V. Support vector networks. Machine Learning 20 3 (1995) 273-297
4. Cvetkovic D., and Cosic I. Sleep onset estimator. Sleep and Biological Rhythms 6 Suppl. 1 (2008) A53
5. Cvetkovic, D., Holland, G., & Cosic, I. (2007). The relationship between EEG, PPG and Oxymetric signal responses during the OSAH events: A pilot sleep study, sleep and biological rhythms 5 (Suppl. 1), A42. [Abstract published in Journal and presented at the WorldSleep07, fifth world sleep congress of the WFSRSMS, Cairns, Australia, September 2007].
6. Cvetkovic D., Übeyli E.D., and Cosic I. Wavelet transform feature extraction from human PPG, ECG and EEG signal responses to ELF PEMF exposures: A pilot study. Digital Signal Processing 18 5 (2008) 861-874
7. Cvetkovic, D., Übeyli, E.D., Holland, G., & Cosic, I. (in press). Alterations in sleep EEG activity during the hypopnoea episodes. Journal of Medical Systems. doi: 10.1007/s10916-009-9261-1.
8. Hazarika N., Chen J.Z., Tsoi A.C., and Sergejew A. Classification of EEG signals using the wavelet transform. Signal Processing 59 1 (1997) 61-72
9. Kay S.M. Modern spectral estimation: Theory and application (1988), Prentice Hall, New Jersey
10. Kay S.M., and Marple S.L. Spectrum analysis - A modern perspective. Proceedings of the IEEE 69 (1981) 1380-1419
11. Proakis J.G., and Manolakis D.G. Digital signal processing principles, algorithms, and applications (1996), Prentice Hall, New Jersey
12. Rechtschaffen, A., & Kales, A. (1968). A manual of standardized terminology techniques and scoring system for sleep stages of human subjects. Washington, DC: US Government Printing Office, publication no. 204.
13. Rosso O.A., Figliola A., Creso J., and Serrano E. Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings. Medical and Biological Engineering and Computing 42 4 (2004) 516-523
14. Stoica P., and Moses R. Introduction to spectral analysis (1997), Prentice Hall, New Jersey
15. Suykens J.A.K., and Vandewalle J. Least squares support vector machine classifiers. Neural Processing Letters 9 3 (1999) 293-300
16. Tsujinishi D., and Abe S. Fuzzy least squares support vector machines for multiclass problems. Neural Networks 16 (2003) 785-792
17. Übeyli E.D. Analysis of EEG signals using Lyapunov exponents. Neural Network World 16 3 (2006) 257-273
18. Übeyli E.D. Wavelet/mixture of experts network structure for EEG signals classification. Expert Systems with Applications 34 3 (2008) 1954-1962
19. Übeyli E.D. Analysis of EEG signals by combining eigenvector methods and multiclass support vector machines. Computers in Biology and Medicine 38 1 (2008) 14-22
20. Übeyli E.D. Implementing eigenvector methods/probabilistic neural networks for analysis of EEG signals. Neural Networks 21 9 (2008) 1410-1417
21. Übeyli E.D. Analysis of EEG signals by implementing eigenvector methods/recurrent neural networks. Digital Signal Processing 19 1 (2009) 134-143
22. Übeyli E.D. Measuring saliency of features representing EEG signals using signal-to-noise ratios. Expert Systems with Applications 36 1 (2009) 501-509
23. Übeyli E.D. Decision support systems for time-varying biomedical signals: EEG signals classification. Expert Systems with Applications 36 2 (2009) 2275-2284
24. Übeyli E.D. Combined neural network model employing wavelet coefficients for EEG signals classification. Digital Signal Processing 19 2 (2009) 297-308
25. Übeyli E.D., Cvetkovic D., and Cosic I. AR spectral analysis technique for human PPG, ECG and EEG signals. Journal of Medical Systems 32 3 (2008) 201-206
26. Vapnik V. The nature of statistical learning theory (1995), Springer-Verlag, New York
27. Vgontzas A.N., and Kales A. Sleep and its disorders. Annual Review of Medicine 50 (1999) 387-400