Computational Intelligence and Neuroscience

Cognitive-Based EEG BCIs and Human Brain-Robot Interactions


Publishing date
26 May 2017
Status
Published
Submission deadline
06 Jan 2017

Lead Editor
Guest Editors

1California State University Bakersfield, Bakersfield, USA

2East China University of Science and Technology, Shanghai, China

3Nankai University, Tianjin, China


Cognitive-Based EEG BCIs and Human Brain-Robot Interactions

Description

Brain computer interface (BCI) technology has been used to help disabled patients for their daily life by controlling external devices by brain activities. Noninvasive BCI systems typically rely on the scalp-recorded electroencephalogram (EEG). Many BCIs require the user to perform specific voluntary tasks to produce distinct EEG patterns, such as paying attention to stimulus or doing some other mental tasks (e.g., motor imagery) , which were related to human cognitive control. It has been applied to controlling intelligent peripherals in brain-robot interaction (BRI), but a number of the issues, such individual differences among subjects, accuracies, and information transfer rate, need to be addressed. In addition, developing shared control approaches by combining human intelligence and machine intelligence is important to improve the performance of BRI systems.

The aim of this special issue is to call for high-quality research articles as well as review articles with a focus on human cognitive mechanism to improve recognition performance of evoked EEG potentials and on smart brain-robot interaction.

Potential topics include but are not limited to the following:

  • Acquisition methods of brain signals
  • System designs for brain signal acquisition
  • Brain computer interface paradigm based on human cognitive processes
  • Closed loop control for subject and decoder learning in BCI system
  • New decoding strategies of EEG-based paradigms (SSVEP, P300, N200, motor imagery, hybrid, etc.)
  • Improvement of brain signal information transfer rate
  • Processing methods for feature extraction and classification
  • Interactive approaches between brain and robot
  • Machine vision for BRI application
  • Integration of human and machine intelligence
  • Real-world applications

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 9471841
  • - Editorial

Cognitive-Based EEG BCIs and Human Brain-Robot Interactions

Wei Li | Jing Jin | Feng Duan
  • Special Issue
  • - Volume 2017
  • - Article ID 5468208
  • - Research Article

Object Extraction in Cluttered Environments via a P300-Based IFCE

Xiaoqian Mao | Wei Li | ... | Genshe Chen
  • Special Issue
  • - Volume 2017
  • - Article ID 5863512
  • - Research Article

Development of a Novel Motor Imagery Control Technique and Application in a Gaming Environment

Ting Li | Jinhua Zhang | ... | Baozeng Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 1323985
  • - Research Article

Comparison of the BCI Performance between the Semitransparent Face Pattern and the Traditional Face Pattern

Jiao Cheng | Jing Jin | Xingyu Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 1742862
  • - Review Article

Progress in EEG-Based Brain Robot Interaction Systems

Xiaoqian Mao | Mengfan Li | ... | Genshe Chen
  • Special Issue
  • - Volume 2017
  • - Article ID 9528097
  • - Research Article

An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

Jinyi Long | Jue Wang | Tianyou Yu
  • Special Issue
  • - Volume 2016
  • - Article ID 2637603
  • - Research Article

Low-Rank Linear Dynamical Systems for Motor Imagery EEG

Wenchang Zhang | Fuchun Sun | ... | Shaobo Liu
Computational Intelligence and Neuroscience
 Journal metrics
Acceptance rate28%
Submission to final decision79 days
Acceptance to publication37 days
CiteScore4.700
Impact Factor2.284
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