| |
 |
UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS Guest
2024-11-23 18:07 |
 |
|
|
|
Conference: Bucharest University Faculty of Physics 2023 Meeting
Section: Biophysics; Medical Physics
Title:
The analysis of SEEG data in epileptic patients using computational methods
Authors:
Daria-Andreea DRAGOTOIU-RADUȚĂ, Andrei BARBORICĂ
*
Affiliation:
University of Bucharest, Faculty of Physics, 405 Atomistilor Street, P.O. Box MG-11, 077125 Magurele, Romania
E-mail
dariandreea74@gmail.com
Keywords:
SEEG data, Epileptic activity, Empirical mode decomposition, Hilbert transform
Abstract:
Epilepsy, a neurological disorder characterized by recurrent seizures, necessitates thorough analysis of intracranial electroencephalography (SEEG) data to comprehend underlying mechanisms and guide therapeutic interventions.In this study, we propose a novel approach that combines Empirical Mode Decomposition (EMD) and Hilbert transform for the analysis of SEEG data in an epileptic patient.
EMD has been proven to be a powerful tool for analyzing nonlinear and non-stationary signals. It is a data-driven technique that decomposes signals into intrinsic mode functions (IMFs) of different timescales. By adaptively extracting oscillatory components, EMD enables identification of frequency bands within SEEG data, crucial for characterizing epileptic activity. Hilbert transform complements this by analyzing instantaneous amplitude and phase.
We apply EMD to decompose SEEG data into IMFs, effectively separating frequency components. Subsequently, we utilize Hilbert transform on each IMF to extract instantaneous amplitude and phase, enabling identification and tracking of transient events and temporal dynamics within each frequency band.
References:
Huang, Norden E., et al. "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis." Proceedings of the Royal Society of London. Series A: mathematical, physical and engineering sciences 454.1971 (1998): 903-995
MATLAB - The Mathworks, Natick, MA, http://www.mathworks.com.
Lyons, Richard. "Understanding digital signal processing's frequency domain." RF DESIGN 24.11 (2001): 36-49.
Schelter, Bjorn, Matthias Winterhalder, and Jens Timmer. Handbook of time series analysis. Wiley-VCH, Berlin, 2006.
Pachori, Ram Bilas. "Discrimination between ictal and seizure-free EEG signals using empirical mode decomposition." Research Letters in Signal Processing 2008 (2008).
Rehman & Mandic, Multivariate Empirical Mode Decomposition, Proceedings of the Royal Society A, vol. 466, no. 2117, pp. 1291-1302, 2010.
|
|
|
|