A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update
Objective. Most current electroencephalography (EEG)-based brain–computer interfaces
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …
Measuring and computing cognitive statuses of construction workers based on electroencephalogram: a critical review
Construction workers' cognitive statuses affecting their safety and productivity are essential
for successful construction management. Electroencephalogram (EEG) provides a potential …
for successful construction management. Electroencephalogram (EEG) provides a potential …
A deep transfer convolutional neural network framework for EEG signal classification
Nowadays, motor imagery (MI) electroencephalogram (EEG) signal classification has
become a hotspot in the research field of brain computer interface (BCI). More recently, deep …
become a hotspot in the research field of brain computer interface (BCI). More recently, deep …
Automated EEG analysis of epilepsy: a review
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 …
Electroencephalogram (EEG) is a test that measures and records the electrical activity of the …
Automated diagnosis of epileptic EEG using entropies
UR Acharya, F Molinari, SV Sree… - … signal processing and …, 2012 - Elsevier
Epilepsy is a neurological disorder characterized by the presence of recurring seizures. Like
many other neurological disorders, epilepsy can be assessed by the electroencephalogram …
many other neurological disorders, epilepsy can be assessed by the electroencephalogram …
Bispectrum-based channel selection for motor imagery based brain-computer interfacing
The performance of motor imagery (MI) based Brain-computer interfacing (BCI) is easily
affected by noise and redundant information that exists in the multi-channel …
affected by noise and redundant information that exists in the multi-channel …
CWT based transfer learning for motor imagery classification for brain computer interfaces
Background The processing of brain signals for Motor imagery (MI) classification to have
better accuracy is a key issue in the Brain-Computer Interface (BCI). While conventional …
better accuracy is a key issue in the Brain-Computer Interface (BCI). While conventional …
[HTML][HTML] Revealing real-time emotional responses: a personalized assessment based on heartbeat dynamics
Emotion recognition through computational modeling and analysis of physiological signals
has been widely investigated in the last decade. Most of the proposed emotion recognition …
has been widely investigated in the last decade. Most of the proposed emotion recognition …
A driver fatigue recognition model based on information fusion and dynamic Bayesian network
G Yang, Y Lin, P Bhattacharya - Information Sciences, 2010 - Elsevier
We propose a driver fatigue recognition model based on the dynamic Bayesian network,
information fusion and multiple contextual and physiological features. We include features …
information fusion and multiple contextual and physiological features. We include features …
A csp\am-ba-svm approach for motor imagery bci system
Brain-computer interface (BCI) has become extremely popular in recent decades. It gained
its significance from the intention of helping paralyzed people communicate with the external …
its significance from the intention of helping paralyzed people communicate with the external …