Seizures

Electroencephalographic markers of robot-aided therapy in stroke patients for the evaluation of upper limb rehabilitation.

Stroke is the leading cause of permanent disability in developed countries; its effects may include sensory, motor, and cognitive impairment as well as a reduced ability to perform self-care and participate in social and community activities. A number of studies have shown that the use of robotic systems in upper limb motor rehabilitation programs provides safe and intensive treatment to patients ...

Automated Identification of Abnormal Adult EEGs.

The interpretation of electroencephalograms (EEGs) is a process that is still dependent on the subjective analysis of the examiners. Though interrater agreement on critical events such as seizures is high, it is much lower on subtler events (e.g., when there are benign variants). The process used by an expert to interpret an EEG is quite subjective and hard to replicate by machine. The performance...

Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.

In this paper, experimental neurophysiologic recording and statistical analysis are combined to investigate the nonlinear characteristic and the cogni...

EEG error potentials detection and classification using time-frequency features for robot reinforcement learning.

In thought-based steering of robots, error potentials (ErrP) can appear when the action resulting from the brain-machine interface (BMI) classifier/co...

Optimized echo state networks with leaky integrator neurons for EEG-based microsleep detection.

The performance of a microsleep detection system was calculated in terms of its ability to detect the behavioural microsleep state (1-s epochs) from s...

Support vector machines using EEG features of cross-frequency coupling can predict treatment outcome in Mecp2-deficient mice.

Anti-convulsive drug treatments of epilepsy typically produce varied outcomes from one patient to the next, often necessitating patients to go through...

An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand.

The loss of hand function can result in severe physical and psychosocial impairment. Thus, compensation of a lost hand function using assistive roboti...

[Study on Sleep Staging Based on Support Vector Machines and Feature Selection in Single Channel Electroencephalogram].

Sleep electroencephalogram (EEG) is an important index in diagnosing sleep disorders and related diseases. Manual sleep staging is time-consuming and ...

Nonholonomic mobile system control by combining EEG-based BCI with ANFIS.

Motor imagery EEG-based BCI has advantages in the assistance of human control of peripheral devices, such as the mobile robot or wheelchair, because t...

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

BACKGROUND: Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient...

On the use of convolutional neural networks and augmented CSP features for multi-class motor imagery of EEG signals classification.

Learning the deep structures and unknown correlations is important for the detection of motor imagery of EEG signals (MI-EEG). This study investigates...

Assessing neuro-motor recovery in a stroke survivor with high-resolution EEG, robotics and Virtual Reality.

One post-stroke patient underwent neuro-motor rehabilitation of one upper limb with a novel system combining a passive robotic device, Virtual Reality...

Reverse bi-orthogonal wavelets & fuzzy classifiers for the automatic detection of spike waves in the EEG of the hypoxic ischemic pre-term fetal sheep.

There exists a 6-8 hour window of opportunity for the treatment of perinatal Hypoxic-Ischemic Encephalopathy (HIE) following the original insult after...

Seizure detection using regression tree based feature selection and polynomial SVM classification.

This paper presents a novel patient-specific algorithm for detection of seizures in epileptic patients with low hardware complexity and low power cons...

Convergent Cross Mapping: Basic concept, influence of estimation parameters and practical application.

In neuroscience, data are typically generated from neural network activity. Complex interactions between measured time series are involved, and nothin...

[Development and validation of a new HPLC method for determination of Lamotrigine and clinical application].

BACKGROUND: Lamotrigine is an effective anticonvulsant drug used in the treatment of epilepsy. It has a narrow therapeutic range, a large inter and in...