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Seizures

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Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

Computers in biology and medicine
An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epi...

Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features, which utilized specific characteristics of neural responses. A...

Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the class...

Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

Seizure
PURPOSE: Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ).

Unsupervised Learning of Spike Patterns for Seizure Detection and Wavefront Estimation of High Resolution Micro Electrocorticographic ( $\mu $ ECoG) Data.

IEEE transactions on nanobioscience
For the past few years, we have developed flexible, active, and multiplexed recording devices for high resolution recording over large, clinically relevant areas in the brain. While this technology has enabled a much higher-resolution view of the ele...

Automated analysis of brain activity for seizure detection in zebrafish models of epilepsy.

Journal of neuroscience methods
BACKGROUND: Epilepsy is a chronic neurological condition, with over 30% of cases unresponsive to treatment. Zebrafish larvae show great potential to serve as an animal model of epilepsy in drug discovery. Thanks to their high fecundity and relatively...

Towards Improved Design and Evaluation of Epileptic Seizure Predictors.

IEEE transactions on bio-medical engineering
OBJECTIVE: Key issues in the epilepsy seizure prediction research are (1) the reproducibility of results (2) the inability to compare multiple approaches directly. To overcome these problems, the seizure prediction challenge was organized on Kaggle.c...

Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

eNeuro
Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How do...

Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds.

Journal of pharmacological sciences
Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machin...

Automated seizure detection using limited-channel EEG and non-linear dimension reduction.

Computers in biology and medicine
Electroencephalography (EEG) is an essential component in evaluation of epilepsy. However, full-channel EEG signals recorded from 18 to 23 electrodes on the scalp is neither wearable nor computationally effective. This paper presents advantages of bo...