U-healthcare system: State-of-the-art review and challenges
With the increase of an ageing population and chronic diseases, society becomes more
health conscious and patients become “health consumers” looking for better health …
health conscious and patients become “health consumers” looking for better health …
Converting your thoughts to texts: Enabling brain typing via deep feature learning of eeg signals
An electroencephalography (EEG) based Brain Computer Interface (BCI) enables people to
communicate with the outside world by interpreting the EEG signals of their brains to interact …
communicate with the outside world by interpreting the EEG signals of their brains to interact …
Multi-person brain activity recognition via comprehensive EEG signal analysis
An electroencephalography (EEG) based brain activity recognition is a fundamental field of
study for a number of significant applications such as intention prediction, appliance control …
study for a number of significant applications such as intention prediction, appliance control …
Adaptive seizure onset detection framework using a hybrid PCA–CSP approach
S Khanmohammadi, CA Chou - IEEE journal of biomedical and …, 2017 - ieeexplore.ieee.org
Epilepsy is one of the most common neurological disorders in the world. Prompt detection of
seizure onset from electroencephalogram (EEG) signals can improve the treatment of …
seizure onset from electroencephalogram (EEG) signals can improve the treatment of …
Subject-independent classification of P300 event-related potentials using a small number of training subjects
B Abibullaev, K Kunanbayev… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The intersubject variability present in electroencephalographic (EEG) signals can affect the
performance of the brain–computer interface (BCI) systems. Despite the significant progress …
performance of the brain–computer interface (BCI) systems. Despite the significant progress …
Effects of task complexity on motor imagery-based brain–computer interface
The performance of electroencephalogram (EEG)-based brain-computer interfaces (BCIs)
still needs improvements for real world applications. An improvement on BCIs could be …
still needs improvements for real world applications. An improvement on BCIs could be …
Design and evaluation of a P300-ERP based BCI system for real-time control of a mobile robot
With the development of Brain-Computer Interface (BCI) systems people with motor
disabilities are able to control external devices using their thoughts. To control a device …
disabilities are able to control external devices using their thoughts. To control a device …
Formulation of a novel classification indices for classification of human hearing abilities according to cortical auditory event potential signals
The classification of brain response signals as per human hearing ability is a complex
undertaking. This study presents a novel formulated index for accurately predicting and …
undertaking. This study presents a novel formulated index for accurately predicting and …
EEG feature selection for thought driven robots using evolutionary algorithms
K Amarasinghe, P Sivils, M Manic - 2016 9th International …, 2016 - ieeexplore.ieee.org
Machine control using electroencephalography (EEG) based brain computer interfaces
(BCI) has been extensively researched in the past decade. However, research is often …
(BCI) has been extensively researched in the past decade. However, research is often …
Periodogram pattern feature-based seizure detection algorithm using optimized hybrid model of MLP and ant colony
M Behnam, H Pourghassem - 2015 23rd Iranian Conference …, 2015 - ieeexplore.ieee.org
Seizure detection with EEG analysis in the form of offline is an application of brain signal
processing. In this paper, a seizure detection algorithm using pattern features of …
processing. In this paper, a seizure detection algorithm using pattern features of …