Cycles in epilepsy
Epilepsy is among the most dynamic disorders in neurology. A canonical view holds that
seizures, the characteristic sign of epilepsy, occur at random, but, for centuries, humans …
seizures, the characteristic sign of epilepsy, occur at random, but, for centuries, humans …
Chronic electroencephalography in epilepsy with a responsive neurostimulation device: current status and future prospects
VR Rao - Expert Review of Medical Devices, 2021 - Taylor & Francis
Introduction Implanted neurostimulation devices are gaining traction as therapeutic options
for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable …
for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable …
Seizure forecasting using minimally invasive, ultra‐long‐term subcutaneous EEG: Generalizable cross‐patient models
This study describes a generalized cross‐patient seizure‐forecasting approach using
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …
recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings …
Diagnostic yield and limitations of in‐hospital documentation in patients with epilepsy
Objective To determine the diagnostic yield of in‐hospital video–electroencephalography
(EEG) monitoring to document seizures in patients with epilepsy. Methods Retrospective …
(EEG) monitoring to document seizures in patients with epilepsy. Methods Retrospective …
A combination of statistical parameters for epileptic seizure detection and classification using VMD and NLTWSVM
S Zhang, G Liu, R Xiao, W Cui, J Cai, X Hu… - Biocybernetics and …, 2022 - Elsevier
The epileptic seizure detection and classification is of great significance for clinical
diagnosis and treatment. To realize the detection and classification of epileptic seizure, this …
diagnosis and treatment. To realize the detection and classification of epileptic seizure, this …
[HTML][HTML] Time in brain: how biological rhythms impact on EEG signals and on EEG-derived brain networks
Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and
is used extensively in various domains, ranging from clinical diagnosis via neuroscience …
is used extensively in various domains, ranging from clinical diagnosis via neuroscience …
Development of Low-Contact-Impedance Dry Electrodes for Electroencephalogram Signal Acquisition
Dry electroencephalogram (EEG) systems have a short set-up time and require limited skin
preparation. However, they tend to require strong electrode-to-skin contact. In this study, dry …
preparation. However, they tend to require strong electrode-to-skin contact. In this study, dry …
[HTML][HTML] Chronobiology of epilepsy and sudden unexpected death in epilepsy
BL Kreitlow, W Li, GF Buchanan - Frontiers in neuroscience, 2022 - frontiersin.org
Epilepsy is a neurological disease characterized by spontaneous, unprovoked seizures.
Various insults render the brain hyperexcitable and susceptible to seizure. Despite there …
Various insults render the brain hyperexcitable and susceptible to seizure. Despite there …
Bilateral temporal lobe epilepsy: How many seizures are required in chronic ambulatory electrocorticography to estimate the laterality ratio?
S Chiang, JM Fan, VR Rao - Epilepsia, 2022 - Wiley Online Library
Objective This study was undertaken to measure the duration of chronic
electrocorticography (ECoG) needed to attain stable estimates of the seizure laterality ratio …
electrocorticography (ECoG) needed to attain stable estimates of the seizure laterality ratio …
Implementation of a morphological filter for removing spikes from the epileptic brain signals to improve identification ripples
Epilepsy is a very common disease affecting at least 1% of the population, comprising a
number of over 50 million people. As many patients suffer from the drug-resistant version …
number of over 50 million people. As many patients suffer from the drug-resistant version …