AIMC Topic: Event-Related Potentials, P300

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Leveraging Deep Learning Techniques to Improve P300-Based Brain Computer Interfaces.

IEEE journal of biomedical and health informatics Oct 4, 2022
Brain-Computer Interface (BCI) has become an established technology to interconnect a human brain and an external device. One of the most popular protocols for BCI is based on the extraction of the so-called P300 wave from electroencephalography (EEG...
Deep Learning Electroencephalography Brain-Computer Interfaces Event-Related Potentials, P300 Humans Neural Networks, Computer Algorithms
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The Effect of the Graphic Structures of Humanoid Robot on N200 and P300 Potentials.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 20, 2020
Humanoid robots are widely used in brain computer interface (BCI). Using a humanoid robot stimulus could increase the amplitude of event-related potentials (ERPs), which improves BCI performance. Since a humanoid robot contains many human elements, t...
Electroencephalography Brain-Computer Interfaces Photic Stimulation Evoked Potentials Humans Brain Robotics 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...
Robotics Electroencephalography Signal Processing, Computer-Assisted Goals Brain-Computer Interfaces Proof of Concept Study Event-Related Potentials, P300 Young Adult Biomechanical Phenomena Male Models, Theoretical Artificial Intelligence Brain Female Motor Activity Mental Fatigue Imagination Humans
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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...
Male Middle Aged Depressive Disorder, Major Stress Disorders, Post-Traumatic Electroencephalography Humans Cerebral Cortex Event-Related Potentials, P300 Machine Learning Female Adult
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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...
Event-Related Potentials, P300 Communication Devices for People with Disabilities Neural Networks, Computer Algorithms User-Computer Interface Brain-Computer Interfaces Humans
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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...
Deep Learning Models, Theoretical Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Event-Related Potentials, P300 Imagination Humans Neural Networks, Computer Machine Learning Algorithms Reproducibility of Results
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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...
Humans Male Cognitive Dysfunction Models, Theoretical Electroencephalography Neural Networks, Computer Female Aged Event-Related Potentials, P300 Alzheimer Disease Cerebral Cortex Evoked Potentials, Auditory
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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...
Electroencephalography Intelligence Brain-Computer Interfaces Vision, Ocular Image Processing, Computer-Assisted Fuzzy Logic Robotics Event-Related Potentials, P300 Evoked Potentials, Somatosensory Humans Artificial Intelligence Algorithms
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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...
Young Adult Adult Male Middle Aged Brain-Computer Interfaces Deep Learning Event-Related Potentials, P300 Humans Electroencephalography Communication Devices for People with Disabilities Algorithms Signal Processing, Computer-Assisted Female
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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 Adolescent Female Humans Brain-Computer Interfaces Young Adult Electroencephalography Adult Neural Networks, Computer Evoked Potentials, Visual Male Algorithms Movement Event-Related Potentials, P300
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