[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …
A review of epileptic seizure detection using machine learning classifiers
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain
signals produced by brain neurons. Neurons are connected to each other in a complex way …
signals produced by brain neurons. Neurons are connected to each other in a complex way …
A review on mental stress assessment methods using EEG signals
Mental stress is one of the serious factors that lead to many health problems. Scientists and
physicians have developed various tools to assess the level of mental stress in its early …
physicians have developed various tools to assess the level of mental stress in its early …
[HTML][HTML] Cognitive neuroscience and robotics: Advancements and future research directions
In recent years, brain-based technologies that capitalise on human abilities to facilitate
human–system/robot interactions have been actively explored, especially in brain robotics …
human–system/robot interactions have been actively explored, especially in brain robotics …
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022 - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
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 …
[Retracted] Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches
Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health.
It occurs abruptly without any symptoms and thus increases the mortality rate of humans …
It occurs abruptly without any symptoms and thus increases the mortality rate of humans …
Epileptic-seizure classification using phase-space representation of FBSE-EWT based EEG sub-band signals and ensemble learners
Electroencephalogram (EEG) signals are non-linear and non-stationary in nature. The
phase-space representation (PSR) method is useful for analysing the non-linear …
phase-space representation (PSR) method is useful for analysing the non-linear …
Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
P Moridian, A Shoeibi, M Khodatars… - … : Data Mining and …, 2022 - Wiley Online Library
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
Modified binary salp swarm algorithm in EEG signal classification for epilepsy seizure detection
Epilepsy is a brain disorder characterized by sudden seizures, periodic abnormal and
inappropriate behaviour, and an altered state of consciousness. The visual diagnosis of …
inappropriate behaviour, and an altered state of consciousness. The visual diagnosis of …