AIMC Topic: Electroencephalography

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Decoding electroencephalographic signals for direction in brain-computer interface using echo state network and Gaussian readouts.

Computers in biology and medicine Jun 1, 2019
BACKGROUND: Noninvasive brain-computer interfaces (BCI) for movement control via an electroencephalogram (EEG) have been extensively investigated. However, most previous studies decoded user intention for movement directions based on sensorimotor rhy...
Humans Male Models, Neurological Electroencephalography Brain-Computer Interfaces Machine Learning Brain Adult
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Use of Multiple EEG Features and Artificial Neural Network to Monitor the Depth of Anesthesia.

Sensors (Basel, Switzerland) May 31, 2019
The electroencephalogram (EEG) can reflect brain activity and contains abundant information of different anesthetic states of the brain. It has been widely used for monitoring depth of anesthesia (DoA). In this study, we propose a method that combine...
Female Consciousness Monitors Young Adult Monitoring, Physiologic Middle Aged Adult Anesthesia Humans Electroencephalography Adolescent Male Entropy Propofol Neural Networks, Computer Algorithms
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Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal.

Journal of affective disorders May 28, 2019
BACKGROUND: Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS) treatment is an important purpose that eliminates financial and psychological consequences of applying inefficient therapy. To achieve this goal we p...
Sensitivity and Specificity Male Middle Aged Electroencephalography Prognosis Transcranial Magnetic Stimulation Depressive Disorder, Major Humans Female Treatment Outcome Machine Learning Adult Algorithms
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Applications of deep learning for the analysis of medical data.

Archives of pharmacal research May 28, 2019
Over the past decade, deep learning has demonstrated superior performances in solving many problems in various fields of medicine compared with other machine learning methods. To understand how deep learning has surpassed traditional machine learning...
Datasets as Topic Stomach Electroencephalography Seizures Radiographic Image Interpretation, Computer-Assisted Humans Data Analysis Big Data Computational Biology Drug Discovery Deep Learning
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FusionAtt: Deep Fusional Attention Networks for Multi-Channel Biomedical Signals.

Sensors (Basel, Switzerland) May 28, 2019
Recently, pervasive sensing technologies have been widely applied to comprehensive patient monitoring in order to improve clinical treatment. Various types of biomedical signals collected by different sensing channels provide different aspects of pat...
Electroencephalography Signal Processing, Computer-Assisted Attention Databases as Topic Biomedical Technology Neural Networks, Computer Algorithms ROC Curve Humans Support Vector Machine
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Class discrepancy-guided sub-band filter-based common spatial pattern for motor imagery classification.

Journal of neuroscience methods May 26, 2019
BACKGROUND: Motor imagery classification, an important branch of brain-computer interface (BCI), recognizes the intention of subjects to control external auxiliary equipment. Therefore, EEG-based motor imagery classification has received increasing a...
Imagination Pattern Recognition, Automated Brain-Computer Interfaces Cerebral Cortex Motor Activity Humans Adult Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted
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Performance evaluation of DWT based sigmoid entropy in time and frequency domains for automated detection of epileptic seizures using SVM classifier.

Computers in biology and medicine May 24, 2019
The electroencephalogram (EEG) signal contains useful information on physiological states of the brain and has proven to be a potential biomarker to realize the complex dynamic behavior of the brain. Epilepsy is a brain disorder described by recurren...
Male Middle Aged Adolescent Support Vector Machine Electroencephalography Child, Preschool Child Brain Female Aged Adult Humans Seizures Databases, Factual Signal Processing, Computer-Assisted
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Prediction of antiepileptic drug treatment outcomes of patients with newly diagnosed epilepsy by machine learning.

Epilepsy & behavior : E&B May 20, 2019
OBJECTIVE: The objective of this study was to build a supervised machine learning-based classifier, which can accurately predict the outcomes of antiepileptic drug (AED) treatment of patients with newly diagnosed epilepsy.
Humans Epilepsy Anticonvulsants Middle Aged Adolescent Treatment Outcome Predictive Value of Tests Electroencephalography Follow-Up Studies Magnetic Resonance Imaging Adult Machine Learning Female Male Algorithms Young Adult Prospective Studies
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A Unified Novel Neural Network Approach and a Prototype Hardware Implementation for Ultra-Low Power EEG Classification.

IEEE transactions on biomedical circuits and systems May 15, 2019
This paper introduces a novel electroencephalogram (EEG) data classification scheme together with its implementation in hardware using an innovative approach. The proposed scheme integrates into a single, end-to-end trainable model a spatial filterin...
Algorithms Electroencephalography Electric Power Supplies Neural Networks, Computer
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A self-organized recurrent neural network for estimating the effective connectivity and its application to EEG data.

Computers in biology and medicine May 15, 2019
OBJECTIVE: Effective connectivity is an important notion in neuroscience research, useful for detecting the interactions between regions of the brain.
Humans Neural Networks, Computer Electronic Data Processing Neural Pathways Nerve Net Brain Models, Neurological Electroencephalography
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