Time-frequency-space localization of epileptic EEG oscillations.

Acta Neurobiol Exp (Wars)

Department of Biomedical Physics, Institute of Experimental Physics, Warsaw University, Poland.

Published: January 2006

This paper presents a hybrid method for localization of oscillatory EEG activity. It consists of two steps: multichannel matching pursuit with complex Gabor dictionary, and LORETA inverse solution. Proposed algorithm was successfully applied to the localization of epileptogenic EEG in a single patient.

Download full-text PDF

Source
http://dx.doi.org/10.55782/ane-2005-1572DOI Listing

Publication Analysis

Top Keywords

time-frequency-space localization
4
localization epileptic
4
epileptic eeg
4
eeg oscillations
4
oscillations paper
4
paper presents
4
presents hybrid
4
hybrid method
4
method localization
4
localization oscillatory
4

Similar Publications

UAV Trajectory Control and Power Optimization for Low-Latency C-V2X Communications in a Federated Learning Environment.

Sensors (Basel)

December 2024

Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B2K3, Canada.

Unmanned aerial vehicle (UAV)-enabled vehicular communications in the sixth generation (6G) are characterized by line-of-sight (LoS) and dynamically varying channel conditions. However, the presence of obstacles in the LoS path leads to shadowed fading environments. In UAV-assisted cellular vehicle-to-everything (C-V2X) communication, vehicle and UAV mobility and shadowing adversely impact latency and throughput.

View Article and Find Full Text PDF

The heterogeneity of concrete is a major challenge for acoustic emission monitoring. A method of active-passive joint acoustic emission monitoring considering the heterogeneity of concrete is presented herein, and the time-frequency-space multi-parameter response characteristics of active and passive acoustic emission signals were studied in relation to the damage evolution of concrete. This method provides an idea of evaluating the damage state of concrete more actively and quantitatively than traditional methods.

View Article and Find Full Text PDF

Cardiac arrest (CA) remains the leading cause of coma, and early arousal recovery indicators are needed to allocate critical care resources properly. High-frequency oscillations (HFOs) of somatosensory evoked potentials (SSEPs) have been shown to indicate responsive wakefulness days following CA. Nonetheless, their potential in the acute recovery phase, where the injury is reversible, has not been tested.

View Article and Find Full Text PDF

A motor imagery EEG (MI-EEG) signal is often selected as the driving signal in an active brain computer interface (BCI) system, and it has been a popular field to recognize MI-EEG images via convolutional neural network (CNN), which poses a potential problem for maintaining the integrity of the time-frequency-space information in MI-EEG images and exploring the feature fusion mechanism in the CNN. However, information is excessively compressed in the present MI-EEG image, and the sequential CNN is unfavorable for the comprehensive utilization of local features. In this paper, a multidimensional MI-EEG imaging method is proposed, which is based on time-frequency analysis and the Clough-Tocher (CT) interpolation algorithm.

View Article and Find Full Text PDF

Background: Chikungunya virus (CHIKV) is an emerging mosquito-borne pathogen circulating in tropical and sub-tropical regions. Although autochthonous transmission has not been reported in Australia, there is a potential risk of local CHIKV outbreaks due to the presence of suitable vectors, global trade, frequent international travel and human adaptation to changes in climate.

Methodology/principal Findings: A time series seasonal decomposition method was used to investigate the seasonality and trend of monthly imported CHIKV cases.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!