BioMed Research International

Brain Computer Interface Systems for Neurorobotics: Methods and Applications


Status
Published

1Universidade de Fortaleza, Fortaleza, Brazil

2Kaunas University of Technology, Kaunas, Lithuania

3University of Beira Interior, Covilhã, Portugal

4Ciência e Tecnologia do Ceará, Fortaleza, Brazil


Brain Computer Interface Systems for Neurorobotics: Methods and Applications

Description

Brain computer interface (BCI) systems establish a direct communication between the brain and an external device. These systems can be used for entertainment, to improve the quality of life of patients and to control Virtual Reality applications, industrial machines, and robots. In the neuroscience field such as in neurorehabilitation, BCIs are integrated into controlled virtual environments used for the treatment of disability, for example, cerebral palsy, Down syndrome, and depression. Its aim is to promote a recovery of brain function lost due to a lesion through noninvasive brain stimulation (brain modulation) in a more accurate and faster manner than the traditional techniques. Neurorobotics combines BCIs with robotics aiming to develop artificial limbs, which can act as real members of human body being controlled from a brain-machine interface. With the advancement of a better understanding of how our brain works, new realistic computational algorithms are being considered, making it possible to simulate and model specific brain functions for the development of new Computational Intelligence algorithms and, finally, BCI for mobile devices/apps.

As an augmentative communication channel, BCI has already attracted considerable research interest thanks to recent advances in neurosciences, wearable biosensors, and data mining. However, to overcome numerous challenges BCI technology still requires research in high-performance and robust signal processing and machine learning algorithms to produce a reliable and stable control signal from nonstationary brain signals to allow development of real-life BCI systems usable across many individuals. Further improvements to BCI systems are necessary to ensure that they can meet the needs of specific user groups such as disabled or impaired people as well as common users.

This special issue focuses on recent advances and future trends in methods and applications of BCI systems evaluated in different fields of knowledge, such as neuroengineering, rehabilitation, psychology, pattern recognition, computational intelligence, machine learning, industrial engineering, control and automation engineering, and robotics. We are seeking theoretical, methodological, and particularly empirical papers dealing with different topics.

Potential topics include but are not limited to the following:

  • Acquisition of brain signals
  • Brain signal processing algorithms
  • Virtual, augmented, and mixed realities
  • Automatic real time detection and diagnosis of disease
  • Neurorobotics
  • Mobile robot navigation
  • Smart home
  • Serious games and gamification
  • Hardware, software, and firmware
  • Communication protocols
  • Applications of BCI for education
  • BCI for entertainment
  • Privacy and security in BCI systems
  • BCI systems for independent and assisted living
  • Usability evaluation of BCI systems

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 2505493
  • - Editorial

Brain Computer Interface Systems for Neurorobotics: Methods and Applications

Victor Hugo C. de Albuquerque | Robertas Damaševičius | ... | Pedro P. Rebouças Filho
  • Special Issue
  • - Volume 2017
  • - Article ID 2181380
  • - Research Article

Auris System: Providing Vibrotactile Feedback for Hearing Impaired Population

Felipe Alves Araujo | Fabricio Lima Brasil | ... | Carlos Eduardo Coelho Freire Batista
  • Special Issue
  • - Volume 2017
  • - Article ID 3591914
  • - Research Article

High-Frequency EEG Variations in Children with Autism Spectrum Disorder during Human Faces Visualization

Celina A. Reis Paula | Camille Reategui | ... | Fabricio Lima Brasil
  • Special Issue
  • - Volume 2017
  • - Article ID 5708937
  • - Research Article

Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

Alkinoos Athanasiou | Ioannis Xygonakis | ... | Panagiotis D. Bamidis
  • Special Issue
  • - Volume 2017
  • - Article ID 1695290
  • - Review Article

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation

Laura Carelli | Federica Solca | ... | Barbara Poletti
  • Special Issue
  • - Volume 2017
  • - Article ID 8317357
  • - Research Article

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain

Ning Zhuang | Ying Zeng | ... | Bin Yan
  • Special Issue
  • - Volume 2017
  • - Article ID 2049094
  • - Research Article

Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection

Zhimin Lin | Ying Zeng | ... | Bin Yan
  • Special Issue
  • - Volume 2017
  • - Article ID 1463512
  • - Research Article

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface

Alyssa M. Batula | Youngmoo E. Kim | Hasan Ayaz
  • Special Issue
  • - Volume 2017
  • - Article ID 8316485
  • - Research Article

Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System

Qiang Gao | Lixiang Dou | ... | Chao Chen
  • Special Issue
  • - Volume 2017
  • - Article ID 7395385
  • - Research Article

A MISO-ARX-Based Method for Single-Trial Evoked Potential Extraction

Nannan Yu | Lingling Wu | ... | Hanbing Lu
BioMed Research International
 Journal metrics
Acceptance rate30%
Submission to final decision66 days
Acceptance to publication35 days
CiteScore3.600
Impact Factor2.276
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