[HTML][HTML] Machine learning for detection of interictal epileptiform discharges
C da Silva Lourenço, MC Tjepkema-Cloostermans… - Clinical …, 2021 - Elsevier
The electroencephalogram (EEG) is a fundamental tool in the diagnosis and classification of
epilepsy. In particular, Interictal Epileptiform Discharges (IEDs) reflect an increased …
epilepsy. In particular, Interictal Epileptiform Discharges (IEDs) reflect an increased …
Automated epileptic seizure detection methods: a review study
Epilepsy is a neurological disorder with prevalence of about 1-2% of the world's population
(Mormann, Andrzejak, Elger & Lehnertz, 2007). It is characterized by sudden recurrent and …
(Mormann, Andrzejak, Elger & Lehnertz, 2007). It is characterized by sudden recurrent and …
[PDF][PDF] Bibliography of self-organizing map (SOM) papers: 1998–2001 addendum
Abstract The Self-Organizing Map (SOM) algorithm has attracted a great deal of interest
among researches and practitioners in a wide variety of fields. The SOM has been analyzed …
among researches and practitioners in a wide variety of fields. The SOM has been analyzed …
Automated real-time epileptic seizure detection in scalp EEG recordings using an algorithm based on wavelet packet transform
AS Zandi, M Javidan, GA Dumont… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
A novel wavelet-based algorithm for real-time detection of epileptic seizures using scalp
EEG is proposed. In a moving-window analysis, the EEG from each channel is decomposed …
EEG is proposed. In a moving-window analysis, the EEG from each channel is decomposed …
[HTML][HTML] A review of signal processing and machine learning techniques for interictal epileptiform discharge detection
Brain interictal epileptiform discharges (IEDs), as one of the hallmarks of epileptic brain, are
transient events captured by electroencephalogram (EEG). IEDs are generated by seizure …
transient events captured by electroencephalogram (EEG). IEDs are generated by seizure …
Deep learning for automated epileptiform discharge detection from scalp EEG: A systematic review
Automated interictal epileptiform discharge (IED) detection has been widely studied, with
machine learning methods at the forefront in recent years. As computational resources …
machine learning methods at the forefront in recent years. As computational resources …
[HTML][HTML] Bio-signal based control in assistive robots: a survey
Recently, bio-signal based control has been gradually deployed in biomedical devices and
assistive robots for improving the quality of life of disabled and elderly people, among which …
assistive robots for improving the quality of life of disabled and elderly people, among which …
Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks
This paper introduces a three-stage procedure based on artificial neural networks for the
automatic detection of epileptiform events (EVs) in a multichannel electroencephalogram …
automatic detection of epileptiform events (EVs) in a multichannel electroencephalogram …
Efficient unsupervised algorithms for the detection of seizures in continuous EEG recordings from rats after brain injury
AM White, PA Williams, DJ Ferraro, S Clark… - Journal of neuroscience …, 2006 - Elsevier
Long-term EEG monitoring in chronically epileptic animals produces very large EEG data
files which require efficient algorithms to differentiate interictal spikes and seizures from …
files which require efficient algorithms to differentiate interictal spikes and seizures from …
Computerized epileptiform transient detection in the scalp electroencephalogram: Obstacles to progress and the example of computerized ECG interpretation
JJ Halford - Clinical Neurophysiology, 2009 - Elsevier
Computerized detection of epileptiform transients (ETs), also called spikes and sharp waves,
in the electroencephalogram (EEG) has been a research goal for the last 40years. A reliable …
in the electroencephalogram (EEG) has been a research goal for the last 40years. A reliable …