AIMC Topic: Electroencephalography
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The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing.
Journal of neuroscience methods
Nov 11, 2016
BACKGROUND: Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong back...
Quantitative EEG Evaluation During Robot-Assisted Foot Movement.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Nov 9, 2016
Passiveand imagined limbmovements induce changes in cerebral oscillatory activity. Central modulatory effects play a role in plastic changes, and are of uttermost importance in rehabilitation. This has extensively been studied for upper limb, but les...
Scale-Dependent Signal Identification in Low-Dimensional Subspace: Motor Imagery Task Classification.
Neural plasticity
Nov 3, 2016
Motor imagery electroencephalography (EEG) has been successfully used in locomotor rehabilitation programs. While the noise-assisted multivariate empirical mode decomposition (NA-MEMD) algorithm has been utilized to extract task-specific frequency ba...
Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 19, 2016
Daytime short nap involves physiological processes, such as alertness, drowsiness and sleep. The study of the relationship between drowsiness and nap based on physiological signals is a great way to have a better understanding of the periodical rhyme...
Sleep Stages
Diagnosis, Computer-Assisted
Models, Statistical
Data Interpretation, Statistical
Bayes Theorem
Electroencephalography
Pattern Recognition, Automated
Polysomnography
Young Adult
Adult
Sensitivity and Specificity
Male
Computer Simulation
Humans
Female
Machine Learning
Reproducibility of Results
Algorithms
Automatic Diagnosis of Obstructive Sleep Apnea/Hypopnea Events Using Respiratory Signals.
Journal of medical systems
Oct 19, 2016
Obstructive sleep apnea is a sleep disorder which may lead to various results. While some studies used real-time systems, there are also numerous studies which focus on diagnosing Obstructive Sleep Apnea via signals obtained by polysomnography from a...
Beatquency domain and machine learning improve prediction of cardiovascular death after acute coronary syndrome.
Scientific reports
Oct 6, 2016
Frequency domain measures of heart rate variability (HRV) are associated with adverse events after a myocardial infarction. However, patterns in the traditional frequency domain (measured in Hz, or cycles per second) may capture different cardiac phe...
Correlated EEG Signals Simulation Based on Artificial Neural Networks.
International journal of neural systems
Sep 30, 2016
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...
Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks.
BioMed research international
Sep 29, 2016
The design of brain-computer interface for the wheelchair for physically disabled people is presented. The design of the proposed system is based on receiving, processing, and classification of the electroencephalographic (EEG) signals and then perfo...
A Realistic Seizure Prediction Study Based on Multiclass SVM.
International journal of neural systems
Sep 23, 2016
A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-...
LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 20, 2016
Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical ...
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