Kalman smoother based time-varying spectrum estimation of EEG during single agent propofol anesthesia

Author

Georgiadis, S.D. ; Tarvainen, M.P. ; Kaskinoro, K. ; Maksimow, A. ; Kärki, T. ; Jääskeläinen, S. ; Scheinin, H. ; Karjalainen, P.A.

Author_Institution

Dept. of Phys., Univ. of Kuopio, Kuopio, Finland

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

5709

Lastpage

5712

Abstract

A time-varying parametric spectrum estimation method for analyzing EEG dynamics is presented. EEG signals are first modeled as a time-varying auto-regressive stochastic process and the model parameters are estimated recursively with a Kalman smoother algorithm. Time-varying spectrum estimates are then obtained from the estimated parameters. The proposed method was applied to measurements collected during low dose propofol anesthesia. The method was able to detect changes of event related (de)synchronization type elicited by verbal command.

Keywords

Kalman filters; autoregressive processes; bioelectric phenomena; drugs; electroencephalography; medical signal processing; neurophysiology; recursive estimation; smoothing methods; spectral analysis; synchronisation; EEG dynamics; EEG signal model; Kalman smoother; autoregressive stochastic process; event related synchronization detection; recursive estimation; single agent propofol anesthesia; time-varying parametric spectrum estimation; verbal command; Adult; Algorithms; Anesthetics, Intravenous; Brain; Electroencephalography; Humans; Male; Pattern Recognition, Automated; Propofol; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Young Adult;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5332660

Filename

5332660