Robust linear predictor as EEG fluctuation analyzer in diagnosis of Alzheimer's disease

• Autorzy: Zachová D. , Kukal J. , Vyšata O.
• Języki publikacji: EN

Abstrakty

EN

The paper is oriented to EEG signal analysis, which is focused to quasi-stationarity hypothesis that the statistical properties of the channel signal fluctuate in time. Robust linear predictor is used for short segments of EEG as low-pass filter and the difference between the raw EEG and filter output was subject of statistical testing. Novelty is in the fluctuation measurement which enables to classify the Alzheimer's disease patients against controls.

Słowa kluczowe

EN

Alzheimer's diseases; EEG; quasi-stationarity; linear predictor; robust identification

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2011
• Tom: Vol. 21, no. 2
• Strony: 121--133
• Opis fizyczny: Bibliogr. 6 poz., rys., tab.

Twórcy

autor

Zachová D.

autor

Kukal J.

autor

Vyšata O.

• FNSPE, CTU, Prague, Czech Rep.

Bibliografia

• [1] T. FAWCETT: An Introduction to ROC analysis. In „Pattern Recognition Letters (Amsterdam, 2006)”, 27 Elsevier Science, (2006), 861-876.
• [2] P. J. HUBER and E. M. RONCHETTI: Robust Statistic. John Wiley & Sons, Hobo-ken, 2009.
• [3] R. G. Lehr and A. Pong: ROC Curve. In Encycłopedia of Biopharmaceutical Statistics (New York, 2003) Marcel Dekker, (2003), 884-891.
• [4] M. Meloun and J. Militky: The statislical analysis of experimental data . Academia, Praha, 1998.
• [5] E. Niedermeyer and F. Lopes Da. Silva: Electroencephalography: Basic prin-ciples, clinical applications, and related fields. Lippincott Williams & Wilkins, Philadelphia, 2004.
• [6] M. B. Priestley: Non-linear and Non-stationary Time Senes Analysis. Aca-demic Press, London, 1988.