AIMC Topic: Electroencephalography

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Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features.

Schizophrenia research Jul 15, 2016
Recently, an increasing number of researchers have endeavored to develop practical tools for diagnosing patients with schizophrenia using machine learning techniques applied to EEG biomarkers. Although a number of studies showed that source-level EEG...
Evoked Potentials Auditory Perception Adult Male Diagnosis, Computer-Assisted Psychiatric Status Rating Scales Cognition Electroencephalography Signal Processing, Computer-Assisted Schizophrenia Neuropsychological Tests Humans Machine Learning Female
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Classification Preictal and Interictal Stages via Integrating Interchannel and Time-Domain Analysis of EEG Features.

Clinical EEG and neuroscience Jul 10, 2016
The life quality of patients with refractory epilepsy is extremely affected by abrupt and unpredictable seizures. A reliable method for predicting seizures is important in the management of refractory epilepsy. A critical factor in seizure prediction...
Female Infant, Newborn Reproducibility of Results Sensitivity and Specificity Support Vector Machine Male Disease Progression Diagnosis, Differential Diagnosis, Computer-Assisted Electroencephalography Adolescent Epilepsy Child Pattern Recognition, Automated Humans Algorithms
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Motor Imagery Classification Based on Bilinear Sub-Manifold Learning of Symmetric Positive-Definite Matrices.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 7, 2016
In motor imagery brain-computer interfaces (BCIs), the symmetric positive-definite (SPD) covariance matrices of electroencephalogram (EEG) signals carry important discriminative information. In this paper, we intend to classify motor imagery EEG sign...
Algorithms Reproducibility of Results Sensitivity and Specificity Brain Mapping Electroencephalography Humans Machine Learning Evoked Potentials, Motor Imagination Linear Models Pattern Recognition, Automated Brain-Computer Interfaces Movement
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Assessing the user experience of older adults using a neural network trained to recognize emotions from brain signals.

Journal of biomedical informatics Jul 5, 2016
The use of Ambient Assisted Living (AAL) technologies as a means to cope with problems that arise due to an increasing and aging population is becoming usual. AAL technologies are used to prevent, cure and improve the wellness and health conditions o...
Brain Aged Aged, 80 and over Aging Emotions Humans Neural Networks, Computer Electroencephalography Assisted Living Facilities
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Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

Australasian physical & engineering sciences in medicine Jul 4, 2016
Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine contro...
Brain-Computer Interfaces Task Performance and Analysis Female Adult Male Support Vector Machine Principal Component Analysis Least-Squares Analysis Electroencephalography Signal Processing, Computer-Assisted Humans Pattern Recognition, Automated Neural Networks, Computer Machine Learning
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Real-time multi-channel monitoring of burst-suppression using neural network technology during pediatric status epilepticus treatment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Jun 11, 2016
OBJECTIVE: To develop a real-time monitoring system that has the potential to guide the titration of anesthetic agents in the treatment of pediatric status epilepticus (SE).
Status Epilepticus Child, Preschool Child Humans Monitoring, Physiologic Neural Networks, Computer Electroencephalography Brain Intensive Care Units Female Sensitivity and Specificity Male Adolescent
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Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization.

Computational and mathematical methods in medicine May 30, 2016
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this st...
Adult Principal Component Analysis Humans Healthy Volunteers Signal Transduction Algorithms Electroencephalography Foot Support Vector Machine Signal Processing, Computer-Assisted Computer Simulation Motor Skills Models, Statistical Hand Reproducibility of Results Movement Imagination
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Validation of a novel classification model of psychogenic nonepileptic seizures by video-EEG analysis and a machine learning approach.

Epilepsy & behavior : E&B May 20, 2016
The aim of this study was to validate a novel classification for the diagnosis of PNESs. Fifty-five PNES video-EEG recordings were retrospectively analyzed by four epileptologists and one psychiatrist in a blind manner and classified into four distin...
Video Recording Focus Groups Somatoform Disorders Middle Aged Diagnosis, Differential Single-Blind Method Electroencephalography Seizures Humans Psychiatry Neural Networks, Computer Retrospective Studies Machine Learning Female Male
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Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia.

International journal of neural systems May 3, 2016
A novel technique of quantitative EEG for differentiating patients with early-stage Creutzfeldt-Jakob disease (CJD) from other forms of rapidly progressive dementia (RPD) is proposed. The discrimination is based on the extraction of suitable features...
Aged Sensitivity and Specificity Wavelet Analysis Support Vector Machine Male Creutzfeldt-Jakob Syndrome Humans Diagnosis, Differential Middle Aged Brain Electroencephalography Disease Progression Retrospective Studies Alzheimer Disease Female
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Pattern Classification of Instantaneous Cognitive Task-load Through GMM Clustering, Laplacian Eigenmap, and Ensemble SVMs.

IEEE/ACM transactions on computational biology and bioinformatics May 3, 2016
The identification of the temporal variations in human operator cognitive task-load (CTL) is crucial for preventing possible accidents in human-machine collaborative systems. Recent literature has shown that the change of discrete CTL level during hu...
Humans Machine Learning Software Algorithms Young Adult Adult Psychophysics Male Computational Biology Cluster Analysis Cognition Electroencephalography Support Vector Machine Workload Pattern Recognition, Automated Task Performance and Analysis
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