A comprehensive comparison of handcrafted features and convolutional autoencoders for epileptic seizures detection in EEG signals
Epilepsy, a brain disease generally associated with seizures, has tremendous effects on
people's quality of life. Diagnosis of epileptic seizures is commonly performed on …
people's quality of life. Diagnosis of epileptic seizures is commonly performed on …
Schizophrenia recognition based on the phase space dynamic of EEG signals and graphical features
Schizophrenia is a mental disorder that causes adverse effects on the mental capacity of a
person, emotional inclinations, and quality of personal and social life. The official statistics …
person, emotional inclinations, and quality of personal and social life. The official statistics …
Epileptic seizure detection using 1 D-convolutional long short-term memory neural networks
Advances in deep learning methods present new opportunities for fixing complex problems
for an end to end learning. In terms of optimal design, seizure detection from EEG data has …
for an end to end learning. In terms of optimal design, seizure detection from EEG data has …
A novel computer-aided diagnosis framework for EEG-based identification of neural diseases
Recent advances in electroencephalogram (EEG) signal classification have primarily
focused on domain-specific approaches, which impede algorithm cross-discipline capability …
focused on domain-specific approaches, which impede algorithm cross-discipline capability …
Performance evaluation of discrete wavelet transform, and wavelet packet decomposition for automated focal and generalized epileptic seizure detection
NJ Sairamya, MJ Premkumar, ST George… - IETE Journal of …, 2021 - Taylor & Francis
In the past decades, wavelet transforms are widely employed for characterizing the
electroencephalogram (EEG) signals for automatic diagnosis of epileptic seizure. But few …
electroencephalogram (EEG) signals for automatic diagnosis of epileptic seizure. But few …
Automatic detection for epileptic seizure using graph-regularized nonnegative matrix factorization and Bayesian linear discriminate analysis
Epilepsy is a neurological disorder characterized by excessive neuronal discharge which
results in many problems in terms of behavior, state of mind, consciousness, and can …
results in many problems in terms of behavior, state of mind, consciousness, and can …
[HTML][HTML] Changes in physiological network connectivity of body system in narcolepsy during REM sleep
Background Narcolepsy is marked by pathologic symptoms including excessive daytime
drowsiness and lethargy, even with sufficient nocturnal sleep. There are two types of …
drowsiness and lethargy, even with sufficient nocturnal sleep. There are two types of …
EEG—Single-channel envelope synchronisation and classification for seizure detection and prediction
JB Romaine, M Pereira Martín, JR Salvador Ortiz… - Brain Sciences, 2021 - mdpi.com
This paper tackles the complex issue of detecting and classifying epileptic seizures whilst
maintaining the total calculations at a minimum. Where many systems depend on the …
maintaining the total calculations at a minimum. Where many systems depend on the …
Automatic identification of epileptic seizures using volume of phase space representation
R Krishnaprasanna, V Vijaya Baskar… - … Engineering Sciences in …, 2021 - Springer
Epilepsy is a neurological disorder that affects people of any age, which can be detected by
Electroencephalogram (EEG) signals. This paper proposes a novel method called Volume …
Electroencephalogram (EEG) signals. This paper proposes a novel method called Volume …
Using computational models and clinical data from depth electrode implants to evaluate active probing paradigms in epilepsy
VR Carvalho - 2021 - repositorio.ufmg.br
Crises espontâneas recorrentes são a marca registrada da epilepsia, uma doença
neurológica que afeta cerca de 1% da população mundial e tem maior incidência em países …
neurológica que afeta cerca de 1% da população mundial e tem maior incidência em países …