AIMC Topic: Electroencephalography

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Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

IEEE journal of biomedical and health informatics Jul 4, 2017
Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain-computer interface applicati...
Humans Signal Processing, Computer-Assisted Artifacts Brain-Computer Interfaces Brain Support Vector Machine Electroencephalography
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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 Jun 22, 2017
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...
Time Factors Electroencephalography Nonlinear Dynamics Brain Waves Neural Networks, Computer Humans Algorithms Computer Simulation
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A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems.

Methods (San Diego, Calif.) Jun 22, 2017
EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequency-tagging is an increasingly popular experimental paradigm that efficiently tests brain function by measuring EEG responses to periodic stimulation...
Artifacts Photic Stimulation Algorithms Electroencephalography Humans Machine Learning
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Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing.

Scientific reports Jun 19, 2017
Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growin...
Humans Male Middle Aged Support Vector Machine Biomarkers Female Aged Electroencephalography Frontotemporal Dementia
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Automated analysis of brain activity for seizure detection in zebrafish models of epilepsy.

Journal of neuroscience methods Jun 1, 2017
BACKGROUND: Epilepsy is a chronic neurological condition, with over 30% of cases unresponsive to treatment. Zebrafish larvae show great potential to serve as an animal model of epilepsy in drug discovery. Thanks to their high fecundity and relatively...
Animals Zebrafish Larva Pattern Recognition, Automated Support Vector Machine Pentylenetetrazole Disease Models, Animal Seizures Signal Processing, Computer-Assisted Electroencephalography Epilepsy Automation, Laboratory Brain Sensitivity and Specificity
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Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System.

BioMed research international Jun 1, 2017
A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, "teeth clenching" state detector, and a steady-state visual evoked...
Brain-Computer Interfaces Male Humans Evoked Potentials, Visual Writing Robotics Movement Algorithms Electroencephalography Female Adult
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Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PloS one May 30, 2017
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm ...
Learning Cognition Electroencephalography Likelihood Functions Humans Neural Networks, Computer Algorithms
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A new near-lossless EEG compression method using ANN-based reconstruction technique.

Computers in biology and medicine May 24, 2017
Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compression methods utilize fixed transforms such as discrete cosine transform (DCT) and wavelet and usually c...
Humans Neural Networks, Computer Algorithms Telemedicine Electroencephalography Data Compression Signal Processing, Computer-Assisted
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Auditory prediction errors as individual biomarkers of schizophrenia.

NeuroImage. Clinical May 3, 2017
Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible ...
Female Young Adult Evoked Potentials Adult Auditory Perception Humans Biomarkers Electroencephalography Male Schizophrenia Pattern Recognition, Automated Middle Aged Support Vector Machine
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Towards Improved Design and Evaluation of Epileptic Seizure Predictors.

IEEE transactions on bio-medical engineering May 2, 2017
OBJECTIVE: Key issues in the epilepsy seizure prediction research are (1) the reproducibility of results (2) the inability to compare multiple approaches directly. To overcome these problems, the seizure prediction challenge was organized on Kaggle.c...
Signal Processing, Computer-Assisted Neural Networks, Computer Support Vector Machine Models, Statistical Discriminant Analysis Humans Electroencephalography Seizures
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