Nonparametric spectral analysis with applications to seizure characterization using EEG time series

Understanding the seizure initiation process and its propagation pattern(s) is a critical task in epilepsy research. Characteristics of the pre-seizure electroencephalograms (EEGs) such as oscillating powers and high-frequency activities are believed to be indicative of the seizure onset and spread patterns. In this article, we analyze epileptic EEG time series using nonparametric spectral estimation methods to extract information on seizure-specific power and characteristic frequency [or frequency band(s)]. Because the EEGs may become nonstationary before seizure events, we develop methods for both stationary and local stationary processes. Based on penalized Whittle likelihood, we propose a direct generalized maximum likelihood (GML) and generalized approximate cross-validation (GACV) methods to estimate smoothing parameters in both smoothing spline spectrum estimation of a stationary process and smoothing spline ANOVA time-varying spectrum estimation of a locally stationary process. We also propose permutation methods to test if a locally stationary process is stationary. Extensive simulations indicate that the proposed direct methods, especially the direct GML, are stable and perform better than other existing methods. We apply the proposed methods to the intracranial electroencephalograms (IEEGs) of an epileptic patient to gain insights into the seizure generation process.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS185 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Electromiografía superficial multicanal en músculo tibial anterior

Este estudio piloto compara el coeficiente de correlación de la raíz cuadrática media, la entropía modificada y la divergencia de Kullback - Leibler (DKL) estimadas de las señales obtenidas mediante la aplicación de la técnica de la electromiografia superficial multicanal tomada del músculo Tibial Anterior durante la Máxima Contracción Voluntaria. Se realizó un experimento comparativo entre un grupo de pacientes con Diabetes Mellitus Tipo 2 y un grupo de control. Se encontraron diferencias significativas entre las muestras en la estimación de valores medios de las características mencionadas excepto en la DKL. El experimento se realizó en el marco de las investigaciones del grupo BASPI de la Pontificia Universidad Javeriana donde se logró implementar un protocolo que permite la extracción de información con la técnica electromiografía multicanal.This pilot study compares the correlation coefficient of the root mean square, the modified entropy and Kullback Leibler divergence (KLD) estimated from signals obtained by applying the technique of multichannel surface electromyography taken from tibialis anterior muscle during the maximum voluntary contraction. A comparative experiment between a group of patients with Type 2 Diabetes Mellitus and a control group was conducted, significant differences between the samples in the estimated mean values of the above characteristics except KLD found. The experiment was conducted in the framework of the research group BASPI Javeriana University where he was able to implement a protocol that allows the extraction of information with multichannel electromyographic technique.Magíster en Ingeniería ElectrónicaMaestrí