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Event-Related Potentials, P300

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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
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...

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
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...

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

Computational intelligence and neuroscience
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...

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

NeuroImage. Clinical
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...

EEGNet: a compact convolutional neural network for EEG-based brain-computer interfaces.

Journal of neural engineering
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...

A Hybrid Network for ERP Detection and Analysis Based on Restricted Boltzmann Machine.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detecting and Please provide the correct one analyzing the event-related potential (ERP) remains an important problem in neuroscience. Due to the low signal-to-noise ratio and complex spatio-temporal patterns of ERP signals, conventional methods usua...

Local and Remote Cooperation With Virtual and Robotic Agents: A P300 BCI Study in Healthy and People Living With Spinal Cord Injury.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The development of technological applications that allow people to control and embody external devices within social interaction settings represents a major goal for current and future brain-computer interface (BCI) systems. Prior research has sugges...

Real-time analysis on ensemble SVM scores to reduce P300-Speller intensification time.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In most Brain-Computer Interface systems, especially the P300-Speller, there must be a harmonized balance between the accuracy and the spelling time. One major drawback of the classical 36-choice P300-Speller is the slow rate of character elicitation...

Convolutional Neural Networks with 3D Input for P300 Identification in Auditory Brain-Computer Interfaces.

Computational intelligence and neuroscience
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...

Object Extraction in Cluttered Environments via a P300-Based IFCE.

Computational intelligence and neuroscience
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...