Seizures

Epileptic seizure detection based on the kernel extreme learning machine.

This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal- and wavelet-based features are extracted from epileptic EEG signals. A combined kernel-function-based ELM approach is then proposed for feature classification. To further reduce the compu...

Design of deep convolutional networks for prediction of image rapid serial visual presentation events.

We report in this paper an investigation of convolutional neural network (CNN) models for target prediction in time-locked image rapid serial visual presentation (RSVP) experiment. We investigated CNN models with 11 different designs of convolution filters in capturing spatial and temporal correlations in EEG data. We showed that for both within-subject and cross-subject predictions, the CNN model...

Robot-assisted procedures in pediatric neurosurgery.

OBJECTIVE During the last 3 decades, robotic technology has rapidly spread across several surgical fields due to the continuous evolution of its versa...

Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.

BACKGROUND: Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Si...

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

BACKGROUND AND OBJECTIVE: Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record ...

[A Classification Algorithm for Epileptic Electroencephalogram Based on Wavelet Multiscale Analysis and Extreme Learning Machine].

The automatic classification of epileptic electroencephalogram(EEG)is significant in the diagnosis and therapy of epilepsy.A classification algorithm ...

Simple, rapid and highly sensitive HPLC method for measurement of Lamotrigine in human plasma and its clinical applications.

Spikes in Lamotrigine concentrations levels and associated clinical toxicity may occur unpredictably. This study describes the development and validat...

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine.

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, th...

Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classif...

An unsupervised subject identification technique using EEG signals.

In this work, EEG spectral features of different subjects are uniquely mapped into a 2D feature space. Such distinctive 2D features pave the way to id...

Improve the generalization of emotional classifiers across time by using training samples from different days.

Electroencephalographic (EEG)-based emotion recognition has attracted increasing attention from the field of human-computer interaction (HCI). However...

Emotion classification using single-channel scalp-EEG recording.

Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perce...

Classification of EEG based-mental fatigue using principal component analysis and Bayesian neural network.

This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from ...

Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient.

Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation w...

Detection of steering direction using EEG recordings based on sample entropy and time-frequency analysis.

Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, i...

High-accuracy user identification using EEG biometrics.

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First,...

Automatic seizure detection using correlation integral with nonlinear adaptive denoising and Kalman filter.

The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detecti...

Automatic recognition of pleasant content of odours through ElectroEncephaloGraphic activity analysis.

This study presents a machine learning approach applied to ElectroEnchephaloGraphic (EEG) response in a group of subjects when exposed to a controlled...

[Recognition of Low Arousal Level Electroencephalogram in the Vigilance Based on Wavelet Packet Rhythm and Support Vector Machine].

Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of mon...

Is levetiracetam neuroprotective in neonatal rats with hypoxic ischemic brain injury?

BACKGROUND: The aim of this study was to determine if levetiracetam (LEV) is neuroprotective in neonatal rats with hypoxic-ischemic brain injury (HIBI...