AIMC Topic: Brain Waves

Clear Filters Showing 41 to 50 of 58 articles

Ongoing brain rhythms shape I-wave properties in a computational model.

Brain stimulation
BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous studies have observed a dependence of TMS-induced responses on ongoing brain activity, for instance sensorimotor rhythms. This suggests an opportunity...

Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework.

Artificial intelligence in medicine
Recent technological advances in machine learning offer the possibility of decoding complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines (LSM) to recognize the emotional state of an individual based on EEG data....

Random ensemble learning for EEG classification.

Artificial intelligence in medicine
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rap...

An EEG-based functional connectivity measure for automatic detection of alcohol use disorder.

Artificial intelligence in medicine
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and m...

Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

NeuroImage. Clinical
OBJECTIVE: To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patterns estimated during EEG periods without visible pathological activity.

Time-Varying System Identification Using an Ultra-Orthogonal Forward Regression and Multiwavelet Basis Functions With Applications to EEG.

IEEE transactions on neural networks and learning systems
A new parametric approach is proposed for nonlinear and nonstationary system identification based on a time-varying nonlinear autoregressive with exogenous input (TV-NARX) model. The TV coefficients of the TV-NARX model are expanded using multiwavele...

Progress in EEG-Based Brain Robot Interaction Systems.

Computational intelligence and neuroscience
The most popular noninvasive Brain Robot Interaction (BRI) technology uses the electroencephalogram- (EEG-) based Brain Computer Interface (BCI), to serve as an additional communication channel, for robot control via brainwaves. This technology is pr...

Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.

Journal of neural engineering
OBJECTIVE: Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, ...

Correlated EEG Signals Simulation Based on Artificial Neural Networks.

International journal of neural systems
In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed metho...