AIMC Topic: Event-Related Potentials, P300

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Evaluating a Semiautonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision.

Computational intelligence and neuroscience Nov 27, 2019
In this paper, we evaluate a semiautonomous brain-computer interface (BCI) for manipulation tasks. In such a system, the user controls a robotic arm through motor imagery commands. In traditional process-control BCI systems, the user has to provide t...
Motor Activity Mental Fatigue Imagination Brain-Computer Interfaces Proof of Concept Study Event-Related Potentials, P300 Young Adult Biomechanical Phenomena Male Models, Theoretical Robotics Electroencephalography Signal Processing, Computer-Assisted Goals Humans Artificial Intelligence Brain Female
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Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

NeuroImage. Clinical Sep 5, 2019
BACKGROUND: The development of optimal classification criteria for specific mental disorders which share similar symptoms is an important issue for precise diagnosis. We investigated whether P300 features in both sensor-level and source-level could b...
Cerebral Cortex Event-Related Potentials, P300 Machine Learning Female Adult Male Middle Aged Depressive Disorder, Major Stress Disorders, Post-Traumatic Electroencephalography Humans
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Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through the Recent Developments With Special Focus on Classification Algorithms.

Clinical EEG and neuroscience Apr 18, 2019
Brain-computer interfaces are sophisticated signal processing systems, which directly operate on neuronal signals to identify specific human intents. These systems can be applied to overcome certain disabilities or to enhance the natural capabilities...
Brain-Computer Interfaces Event-Related Potentials, P300 Communication Devices for People with Disabilities Humans Neural Networks, Computer Algorithms User-Computer Interface
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On the Vulnerability of CNN Classifiers in EEG-Based BCIs.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 2, 2019
Deep learning has been successfully used in numerous applications because of its outstanding performance and the ability to avoid manual feature engineering. One such application is electroencephalogram (EEG)-based brain-computer interface (BCI), whe...
Humans Neural Networks, Computer Machine Learning Algorithms Signal Processing, Computer-Assisted Reproducibility of Results Brain-Computer Interfaces Deep Learning Event-Related Potentials, P300 Models, Theoretical Imagination Electroencephalography
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New-Onset Alzheimer's Disease and Normal Subjects 100% Differentiated by P300.

American journal of Alzheimer's disease and other dementias Feb 7, 2019
Previous work has suggested that evoked potential analysis might allow the detection of subjects with new-onset Alzheimer's disease, which would be useful clinically and personally. Here, it is described how subjects with new-onset Alzheimer's diseas...
Neural Networks, Computer Female Aged Male Humans Cerebral Cortex Evoked Potentials, Auditory Event-Related Potentials, P300 Cognitive Dysfunction Models, Theoretical Electroencephalography Alzheimer Disease
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A Brain-Robot Interaction System by Fusing Human and Machine Intelligence.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Feb 4, 2019
This paper presents a new brain-robot interaction system by fusing human and machine intelligence to improve the real-time control performance. This system consists of a hybrid P300 and steady-state visual evoked potential (SSVEP) mode conveying a hu...
Humans Brain-Computer Interfaces Fuzzy Logic Vision, Ocular Robotics Event-Related Potentials, P300 Electroencephalography Artificial Intelligence Evoked Potentials, Somatosensory Intelligence Algorithms Image Processing, Computer-Assisted
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Improving Performance of Devanagari Script Input-Based P300 Speller Using Deep Learning.

IEEE transactions on bio-medical engineering Oct 9, 2018
The performance of an existing Devanagari script (DS) input-based P300 speller with conventional machine learning techniques suffers from low information transfer rate (ITR). This occurs due to its required large size of display, i.e., 8 × 8 row-colu...
Female Young Adult Adult Male Middle Aged Deep Learning Electroencephalography Signal Processing, Computer-Assisted Humans Algorithms Brain-Computer Interfaces Event-Related Potentials, P300 Communication Devices for People with Disabilities
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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...
Movement Event-Related Potentials, P300 Electroencephalography Brain-Computer Interfaces Evoked Potentials, Visual Humans Adult Neural Networks, Computer Male Algorithms Middle Aged Female Adolescent Young Adult
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Convolutional Neural Networks with 3D Input for P300 Identification in Auditory Brain-Computer Interfaces.

Computational intelligence and neuroscience Nov 7, 2017
From allowing basic communication to move through an environment, several attempts are being made in the field of brain-computer interfaces (BCI) to assist people that somehow find it difficult or impossible to perform certain activities. Focusing on...
Electroencephalography Event-Related Potentials, P300 Female Brain-Computer Interfaces Space Perception Humans Male Analysis of Variance Auditory Perception Neural Networks, Computer User-Computer Interface Neuropsychological Tests Time Perception Brain Time Factors
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Object Extraction in Cluttered Environments via a P300-Based IFCE.

Computational intelligence and neuroscience Jun 27, 2017
One of the fundamental issues for robot navigation is to extract an object of interest from an image. The biggest challenges for extracting objects of interest are how to use a machine to model the objects in which a human is interested and extract t...
Lighting Brain-Computer Interfaces Humans Event-Related Potentials, P300 Robotics Color
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