T161. Correlating magnetoencephalography (MEG) and high-density electroencephalography (EEG) with invasive recordings in pediatric patients undergoing epilepsy surgery
Sign Up to like & getrecommendations! Published in 2018 at "Clinical Neurophysiology"
DOI: 10.1016/j.clinph.2018.04.162
Abstract: Introduction Epilepsy surgery is a potentially curative treatment for medically refractory epilepsy (MRE). The goal of epilepsy surgery is the resection of the epileptogenic zone. Before surgery, MEG and scalp EEG are used to estimate… read more here.
Keywords: epilepsy surgery; ieeg; meg; eeg ... See more keywords
Seizure onset zone classification based on imbalanced iEEG with data augmentation
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/aca04f
Abstract: Objective. Identifying the seizure onset zone (SOZ) in patients with focal epilepsy is the critical information required for surgery. However, collecting this information is challenging, time-consuming, and subjective. Some machine learning methods reduce the workload… read more here.
Keywords: method; class; ieeg; augmentation ... See more keywords
A novel method for dynamically altering the surface area of intracranial EEG electrodes
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/acb79f
Abstract: Objective. Intracranial electroencephalogram (iEEG) plays a critical role in the treatment of neurological diseases, such as epilepsy and Parkinson’s disease, as well as the development of neural prostheses and brain computer interfaces. While electrode geometries… read more here.
Keywords: electrode size; method; brain; ieeg ... See more keywords
Analysis of Epileptic iEEG Data by Applying Convolutional Neural Networks to Low-Frequency Scalograms
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DOI: 10.1109/access.2021.3132128
Abstract: In this paper, Convolutional Neural Networks (CNN) method was applied to low frequency scalograms in order to contribute to the development of diagnostic and early diagnosis systems of epileptic intracranial EEG (iEEG) signals of brain… read more here.
Keywords: neural networks; ieeg; frequency; convolutional neural ... See more keywords
Seizure Onset Zone Identification From iEEG: A Review
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DOI: 10.1109/access.2022.3182716
Abstract: This paper discusses the various methods of identifying the seizure onset zone (SOZ) from the intracranial electroencephalography (iEEG) data. Epilepsy, also known as seizure disorder, is a neurological condition caused due to disruption in the… read more here.
Keywords: seizure; identification; onset zone; ieeg ... See more keywords
Continuous Seizure Detection Based on Transformer and Long-Term iEEG
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3199206
Abstract: Automatic seizure detection algorithms are necessary for patients with refractory epilepsy. Many excellent algorithms have achieved good results in seizure detection. Still, most of them are based on discontinuous intracranial electroencephalogram (iEEG) and ignore the… read more here.
Keywords: long term; seizure detection; detection; ieeg ... See more keywords