Automated EEG analysis of epilepsy: a review

UR Acharya, SV Sree, G Swapna, RJ Martis… - Knowledge-Based …, 2013 - Elsevier
Epilepsy is an electrophysiological disorder of the brain, characterized by recurrent seizures.
Electroencephalogram (EEG) is a test that measures and records the electrical activity of the …

A comparative review on sleep stage classification methods in patients and healthy individuals

R Boostani, F Karimzadeh, M Nami - Computer methods and programs in …, 2017 - Elsevier
Background and objective: Proper scoring of sleep stages can give clinical information on
diagnosing patients with sleep disorders. Since traditional visual scoring of the entire sleep …

A driving fatigue feature detection method based on multifractal theory

F Wang, H Wang, X Zhou, R Fu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Driving fatigue seriously threatens traffic safety. In our work, the multifractal detrended
fluctuation analysis (MF-DFA) method is proposed to detect driver fatigue caused by driving …

An automated system for epilepsy detection using EEG brain signals based on deep learning approach

I Ullah, M Hussain, H Aboalsamh - Expert Systems with Applications, 2018 - Elsevier
Epilepsy is a life-threatening and challenging neurological disorder, which is affecting a
large number of people all over the world. For its detection, encephalography (EEG) is a …

Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals

N Michielli, UR Acharya, F Molinari - Computers in biology and medicine, 2019 - Elsevier
Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in
neurological and clinical studies. NCP represents the mental/cognitive human capacity in …

[HTML][HTML] Chaos as an intermittently forced linear system

SL Brunton, BW Brunton, JL Proctor, E Kaiser… - Nature …, 2017 - nature.com
Understanding the interplay of order and disorder in chaos is a central challenge in modern
quantitative science. Approximate linear representations of nonlinear dynamics have long …

[HTML][HTML] A deep learning model for automated sleep stages classification using PSG signals

O Yildirim, UB Baloglu, UR Acharya - International journal of …, 2019 - mdpi.com
Sleep disorder is a symptom of many neurological diseases that may significantly affect the
quality of daily life. Traditional methods are time-consuming and involve the manual scoring …

Emotional state classification from EEG data using machine learning approach

XW Wang, D Nie, BL Lu - Neurocomputing, 2014 - Elsevier
Recently, emotion classification from EEG data has attracted much attention with the rapid
development of dry electrode techniques, machine learning algorithms, and various real …

A novel multi-class EEG-based sleep stage classification system

P Memar, F Faradji - IEEE Transactions on Neural Systems and …, 2017 - ieeexplore.ieee.org
Sleep stage classification is one of the most critical steps in effective diagnosis and the
treatment of sleep-related disorders. Visual inspection undertaken by sleep experts is a time …

[HTML][HTML] A pervasive approach to EEG-based depression detection

H Cai, J Han, Y Chen, X Sha, Z Wang, B Hu, J Yang… - Complexity, 2018 - hindawi.com
Nowadays, depression is the world's major health concern and economic burden worldwide.
However, due to the limitations of current methods for depression diagnosis, a pervasive …