AIMC Topic: Electroencephalography

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Evolving Network Model That Almost Regenerates Epileptic Data.

Neural computation Feb 9, 2017
In many realistic networks, the edges representing the interactions between nodes are time varying. Evidence is growing that the complex network that models the dynamics of the human brain has time-varying interconnections, that is, the network is ev...
Humans Brain Mapping Electroencephalography Epilepsy Nonlinear Dynamics Wavelet Analysis Neural Networks, Computer Algorithms Brain Time Factors
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Automated seizure detection using limited-channel EEG and non-linear dimension reduction.

Computers in biology and medicine Jan 25, 2017
Electroencephalography (EEG) is an essential component in evaluation of epilepsy. However, full-channel EEG signals recorded from 18 to 23 electrodes on the scalp is neither wearable nor computationally effective. This paper presents advantages of bo...
Nonlinear Dynamics Pattern Recognition, Automated Machine Learning Data Interpretation, Statistical Algorithms Humans Diagnosis, Computer-Assisted Reproducibility of Results Electroencephalography Sample Size Sensitivity and Specificity Seizures
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Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation.

PloS one Jan 19, 2017
In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictiona...
Electroencephalography Signal Processing, Computer-Assisted Pattern Recognition, Automated Data Compression Dictionaries as Topic Machine Learning Algorithms Image Processing, Computer-Assisted Electrocardiography Humans Artificial Intelligence
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Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.

Journal of neural engineering Jan 10, 2017
OBJECTIVE: Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, ...
Adult Sensitivity and Specificity Male Unsupervised Machine Learning Humans Female Reproducibility of Results Visual Perception Visual Cortex Brain-Computer Interfaces Evoked Potentials, Visual Statistics as Topic Data Interpretation, Statistical Brain Waves Electroencephalography Signal Processing, Computer-Assisted Pattern Recognition, Automated
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Deep Learning and Insomnia: Assisting Clinicians With Their Diagnosis.

IEEE journal of biomedical and health informatics Jan 9, 2017
Effective sleep analysis is hampered by the lack of automated tools catering to disordered sleep patterns and cumbersome monitoring hardware. In this paper, we apply deep learning on a set of 57 EEG features extracted from a maximum of two EEG channe...
Electroencephalography Signal Processing, Computer-Assisted Sleep Initiation and Maintenance Disorders Polysomnography Adult Male Middle Aged Diagnosis, Computer-Assisted Sleep Stages Humans Machine Learning Female
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Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction: a review.

Journal of neural engineering Jan 9, 2017
Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently ...
Muscle Contraction Evoked Potentials Man-Machine Systems Electroencephalography Electromyography Pattern Recognition, Automated Brain-Computer Interfaces Humans Brain Algorithms Support Vector Machine Muscle, Skeletal Robotics
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EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery.

Medical & biological engineering & computing Dec 19, 2016
Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an ...
Multivariate Analysis Entropy Consciousness Monitors Data Interpretation, Statistical Electroencephalography Neural Networks, Computer Artifacts Reproducibility of Results Algorithms Pattern Recognition, Automated Sensitivity and Specificity Brain Intraoperative Neurophysiological Monitoring Humans Computer Simulation Models, Statistical
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Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity.

Proceedings of the National Academy of Sciences of the United States of America Dec 12, 2016
The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-o...
Humans Machine Learning Computers Brain Female Adult Male Prefrontal Cortex User-Computer Interface Computer Systems Electroencephalography Evoked Potentials
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A novel deep learning approach for classification of EEG motor imagery signals.

Journal of neural engineering Nov 30, 2016
OBJECTIVE: Signal classification is an important issue in brain computer interface (BCI) systems. Deep learning approaches have been used successfully in many recent studies to learn features and classify different types of data. However, the number ...
Movement Sensitivity and Specificity Evoked Potentials, Motor Humans Electroencephalography Imagination Pattern Recognition, Automated Machine Learning Sensorimotor Cortex Brain-Computer Interfaces Algorithms Reproducibility of Results
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EEG and fMRI agree: Mental arithmetic is the easiest form of imagery to detect.

Consciousness and cognition Nov 14, 2016
fMRI and EEG during mental imagery provide alternative methods of detecting awareness in patients with disorders of consciousness (DOC) without reliance on behaviour. Because using fMRI in patients with DOC is difficult, studies increasingly employ E...
Magnetic Resonance Imaging Electroencephalography Awareness Motor Activity Humans Music Adult Machine Learning Mathematical Concepts Male Female Imagination Middle Aged Young Adult Functional Neuroimaging
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