AIMC Topic: Electroencephalography

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Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings.

Journal of neural engineering Sep 13, 2018
OBJECTIVE: We sought to test the performance of three strategies for binary classification (logistic regression, support vector machines, and deep learning) for the problem of predicting successful episodic memory encoding using direct brain recordin...
Theta Rhythm Memory, Episodic Mental Recall Electrodes, Implanted Computer Simulation Deep Learning Logistic Models Electroencephalography Stochastic Processes Support Vector Machine Predictive Value of Tests Humans Algorithms
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Sample Entropy on Multidistance Signal Level Difference for Epileptic EEG Classification.

TheScientificWorldJournal Sep 12, 2018
Epilepsy is a disorder of the brain's nerves as a result of excessive brain cell activity. It is generally characterized by the recurrent unprovoked seizures. This neurological abnormality can be detected and evaluated using Electroencephalogram (EEG...
Electroencephalography Humans Epilepsy Brain Entropy Support Vector Machine
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Human-agent co-adaptation using error-related potentials.

Journal of neural engineering Sep 11, 2018
OBJECTIVE: Error-related potentials (ErrP) have been proposed as an intuitive feedback signal decoded from the ongoing electroencephalogram (EEG) of a human observer for improving human-robot interaction (HRI). While recent demonstrations of this app...
Robotics Electroencephalography Intention Calibration Female Adult Male Evoked Potentials Interpersonal Relations Fixation, Ocular Feedback, Psychological Brain-Computer Interfaces Adaptation, Psychological Motor Skills Humans
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A Novel Method of Segmentation and Classification for Meditation in Health Care Systems.

Journal of medical systems Sep 11, 2018
Meditation improves positivity in behavioral as well as psychological changes, which are brought elucidated by knowing neuro-physiological consequences of meditation. In the field of cognitive science, neuroscience and physiological research, Electro...
Cross-Sectional Studies Support Vector Machine Electroencephalography Meditation Signal Processing, Computer-Assisted Humans Brain-Computer Interfaces Algorithms
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A Wearable Multi-Modal Bio-Sensing System Towards Real-World Applications.

IEEE transactions on bio-medical engineering Sep 4, 2018
Multi-modal bio-sensing has recently been used as effective research tools in affective computing, autism, clinical disorders, and virtual reality among other areas. However, none of the existing bio-sensing systems support multi-modality in a wearab...
Wearable Electronic Devices Electroencephalography Photoplethysmography Equipment Design Humans Electrocardiography Head Movements Evoked Potentials, Visual Brain-Computer Interfaces Machine Learning Monitoring, Physiologic Video Games Algorithms
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EEG-Based Automatic Sleep Staging Using Ontology and Weighting Feature Analysis.

Computational and mathematical methods in medicine Sep 4, 2018
Sleep staging is considered as an effective indicator for auxiliary diagnosis of sleep diseases and related psychiatric diseases, so it attracts a lot of attention from sleep researchers. Nevertheless, sleep staging based on visual inspection of trad...
Automation Biological Ontologies Humans Sleep Stages Data Analysis Female Sleep Male Electroencephalography Artifacts
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Personalized prediction model for seizure-free epilepsy with levetiracetam therapy: a retrospective data analysis using support vector machine.

British journal of clinical pharmacology Sep 3, 2018
AIMS: To predict the probability of a seizure-free (SF) state in patients with epilepsy (PWEs) after treatment with levetiracetam and to identify the clinical and electroencephalographic (EEG) factors that affect outcomes.
Young Adult Adult Sensitivity and Specificity Adolescent Algorithms Precision Medicine Retrospective Studies Epilepsy Seizures Anticonvulsants Levetiracetam Child Support Vector Machine Humans Electroencephalography
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Epilepsy classification using optimized artificial neural network.

Neurological research Aug 29, 2018
OBJECTIVES: An Electroencephalogram (EEG) is the result of co-operative actions performed by brain cells. In other words, it can be defined as the time course of extracellular field potentials that are generated due to the synchronous action of cells...
Humans Neural Networks, Computer Brain Sensitivity and Specificity Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Statistics as Topic Electroencephalography Epilepsy
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Quiet sleep detection in preterm infants using deep convolutional neural networks.

Journal of neural engineering Aug 22, 2018
OBJECTIVE: Neonates spend most of their time asleep. Sleep of preterm infants evolves rapidly throughout maturation and plays an important role in brain development. Since visual labelling of the sleep stages is a time consuming task, automated analy...
Wakefulness Sleep Automation Infant, Premature Sleep Stages Infant, Newborn Humans Male Electroencephalography Neural Networks, Computer Algorithms Brain Female
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EEG-Based Emotion Recognition Using Quadratic Time-Frequency Distribution.

Sensors (Basel, Switzerland) Aug 20, 2018
Accurate recognition and understating of human emotions is an essential skill that can improve the collaboration between humans and machines. In this vein, electroencephalogram (EEG)-based emotion recognition is considered an active research field wi...
Humans Brain Emotions Female Electroencephalography Male Support Vector Machine
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