Progress in Brain Computer Interface: Challenges and Opportunities

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such...

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Published inFrontiers in systems neuroscience Vol. 15; p. 578875
Main Authors Saha, Simanto, Mamun, Khondaker A., Ahmed, Khawza, Mostafa, Raqibul, Naik, Ganesh R., Darvishi, Sam, Khandoker, Ahsan H., Baumert, Mathias
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 25.02.2021
Subjects
brain computer interface
cognitive rehabilitation
electrical/hemodynamic brain signals
hybrid/multimodal BCI
neuroimaging techniques
Neuroscience
neurosensors
brain computer interface
neurosensors
electrical/hemodynamic brain signals
neuroimaging techniques
cognitive rehabilitation
hybrid/multimodal BCI
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Abstract Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
AbstractList Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
Author Ahmed, Khawza
Baumert, Mathias
Khandoker, Ahsan H.
Darvishi, Sam
Mostafa, Raqibul
Saha, Simanto
Naik, Ganesh R.
Mamun, Khondaker A.
AuthorAffiliation 3 Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Department of Computer Science and Engineering, United International University , Dhaka , Bangladesh
5 Healthcare Engineering Innovation Center, Department of Biomedical Engineering, Khalifa University of Science and Technology , Abu Dhabi , United Arab Emirates
4 Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University , Adelaide, SA , Australia
2 Department of Electrical and Electronic Engineering, United International University , Dhaka , Bangladesh
1 School of Electrical and Electronic Engineering, The University of Adelaide , Adelaide, SA , Australia
AuthorAffiliation_xml – name: 2 Department of Electrical and Electronic Engineering, United International University , Dhaka , Bangladesh
– name: 4 Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University , Adelaide, SA , Australia
– name: 3 Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Department of Computer Science and Engineering, United International University , Dhaka , Bangladesh
– name: 1 School of Electrical and Electronic Engineering, The University of Adelaide , Adelaide, SA , Australia
– name: 5 Healthcare Engineering Innovation Center, Department of Biomedical Engineering, Khalifa University of Science and Technology , Abu Dhabi , United Arab Emirates
Author_xml – sequence: 1
  givenname: Simanto
  surname: Saha
  fullname: Saha, Simanto
– sequence: 2
  givenname: Khondaker A.
  surname: Mamun
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– sequence: 3
  givenname: Khawza
  surname: Ahmed
  fullname: Ahmed, Khawza
– sequence: 4
  givenname: Raqibul
  surname: Mostafa
  fullname: Mostafa, Raqibul
– sequence: 5
  givenname: Ganesh R.
  surname: Naik
  fullname: Naik, Ganesh R.
– sequence: 6
  givenname: Sam
  surname: Darvishi
  fullname: Darvishi, Sam
– sequence: 7
  givenname: Ahsan H.
  surname: Khandoker
  fullname: Khandoker, Ahsan H.
– sequence: 8
  givenname: Mathias
  surname: Baumert
  fullname: Baumert, Mathias
BackLink https://www.ncbi.nlm.nih.gov/pubmed/33716680$$D View this record in MEDLINE/PubMed
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Copyright Copyright © 2021 Saha, Mamun, Ahmed, Mostafa, Naik, Darvishi, Khandoker and Baumert.
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Keywords brain computer interface
neurosensors
electrical/hemodynamic brain signals
neuroimaging techniques
cognitive rehabilitation
hybrid/multimodal BCI
Language English
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Edited by: Alessandro E. P. Villa, Neuro-Heuristic Research Group (NHRG), Switzerland
Reviewed by: Dongrui Wu, Huazhong University of Science and Technology, China; David R. Painter, The University of Queensland, Australia
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Snippet Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree...
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SubjectTerms brain computer interface
cognitive rehabilitation
electrical/hemodynamic brain signals
hybrid/multimodal BCI
neuroimaging techniques
Neuroscience
neurosensors
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Title Progress in Brain Computer Interface: Challenges and Opportunities
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