AIMC Journal:
Journal of neural engineering

Showing 191 to 200 of 244 articles

A machine-learning approach to volitional control of a closed-loop deep brain stimulation system.

Journal of neural engineering Nov 16, 2018
OBJECTIVE: Deep brain stimulation (DBS) is a well-established treatment for essential tremor, but may not be an optimal therapy, as it is always on, regardless of symptoms. A closed-loop (CL) DBS, which uses a biosignal to determine when stimulation ...
Humans Machine Learning Aged Deep Brain Stimulation Psychomotor Performance Volition Essential Tremor Aged, 80 and over Male Middle Aged Pilot Projects
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Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.

Journal of neural engineering Oct 24, 2018
OBJECTIVE: Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulat...
Neural Networks, Computer Action Potentials Neurons Brain Waves Thalamus
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On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.

Journal of neural engineering Oct 19, 2018
OBJECTIVE: Real-time myoelectric experimental protocol is considered as a means to quantify usability of myoelectric control schemes. While usability should be considered over time to assure clinical robustness, all real-time studies reported thus fa...
Female Reproducibility of Results Young Adult Adult Humans Neural Networks, Computer Artificial Limbs Healthy Volunteers Psychomotor Performance Male Pattern Recognition, Automated Computer Systems Signal Processing, Computer-Assisted Electromyography
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Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials.

Journal of neural engineering Oct 3, 2018
OBJECTIVE: Steady-state visual evoked potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram (E...
Visual Cortex Healthy Volunteers Brain-Computer Interfaces Evoked Potentials, Visual Photic Stimulation Humans Neural Networks, Computer Machine Learning Algorithms Reproducibility of Results Adult Electroencephalography Signal Processing, Computer-Assisted
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A novel system of SSVEP-based human-robot coordination.

Journal of neural engineering Sep 17, 2018
OBJECTIVE: Human-robot coordination (HRC) aims to enable human and robot to form a tightly coupled system to accomplish a task. One of its important application prospects is to improve the physical function of the disabled. However, the low level of ...
Humans Brain Female Electroencephalography Young Adult Brain-Computer Interfaces Adult Evoked Potentials, Visual Male Photic Stimulation Robotics
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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...
Electrodes, Implanted Theta Rhythm Stochastic Processes Humans Memory, Episodic Algorithms Mental Recall Logistic Models Computer Simulation Support Vector Machine Deep Learning Predictive Value of Tests Electroencephalography
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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...
Feedback, Psychological Motor Skills Evoked Potentials Interpersonal Relations Fixation, Ocular Adult Male Robotics Electroencephalography Intention Calibration Brain-Computer Interfaces Adaptation, Psychological Humans Female
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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 Female Sleep Stages Humans Automation Infant, Newborn Neural Networks, Computer Infant, Premature Male Algorithms Electroencephalography Brain
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EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces.

Journal of neural engineering Jun 22, 2018
OBJECTIVE: Brain-computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given...
Middle Aged Female Evoked Potentials, Visual Humans Adolescent Movement Young Adult Neural Networks, Computer Electroencephalography Event-Related Potentials, P300 Algorithms Adult Brain-Computer Interfaces Male
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Assessing functional connectivity across 3D tissue engineered axonal tracts using calcium fluorescence imaging.

Journal of neural engineering Jun 1, 2018
OBJECTIVE: Micro-tissue engineered neural networks (micro-TENNs) are anatomically-inspired constructs designed to structurally and functionally emulate white matter pathways in the brain. These 3D neural networks feature long axonal tracts spanning d...
Rats Neurons Calcium Neural Networks, Computer Axons Neuroimaging Pregnancy Entropy Tissue Engineering Female Theta Rhythm Cerebral Cortex Animals Delta Rhythm Neural Pathways Fluorescence
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