Brain-Computer Interfaces

Brain-Computer Interfaces

1st Edition - March 10, 2020

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  • Editors: Nick F. Ramsey, José del R. Millán
  • Hardcover ISBN: 9780444639349
  • eBook ISBN: 9780444639332

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Brain-Computer Interfacing, Volume 168, not only gives readers a clear understanding of what BCI science is currently offering, but also describes future expectations for restoring lost brain function in patients. In-depth technological chapters are aimed at those interested in BCI technologies and the nature of brain signals, while more comprehensive summaries are provided in the more applied chapters. Readers will be able to grasp BCI concepts, understand what needs the technologies can meet, and provide an informed opinion on BCI science.

Key Features

  • Explores how many different causes of disability have similar functional consequences (loss of mobility, communication etc.)
  • Addresses how BCI can be of use
  • Presents a multidisciplinary review of BCI technologies and the opportunities they provide for people in need of a new kind of prosthetic
  • Offers a comprehensive, multidisciplinary review of BCI for researchers in neuroscience and traumatic brain injury that is also ideal for clinicians in neurology and neurosurgery


Basic and clinical researchers in neuroscience and traumatic brain injury; fellows, residents, and practicing clinicians in neurology and neurosurgery; researchers in engineering focusing on brain-computer interfacing

Table of Contents

  • 1. Human brain function and brain-computer interfaces
    2. Brain-computer interfaces: definitions and principles
    3. Stroke and potential benefits of brain to computer interface
    4. Brain-computer interfaces for people with amyotrophic lateral sclerosis
    5. Brain damage by trauma
    6. Spinal cord lesions
    7. Brain-computer interfaces for communication
    8. Applications of brain-computer interfaces to the control of robotic and prosthetic arms
    9. BCI for rehab (‘not control’)
    10. Video games as rich environments to foster brain plasticity
    11. Consciousness and communication brain:computer interfaces in severely brain-injured patients
    12. Smart neuromodulation in movement disorders
    13. Bidirectional brain computer interfaces
    14. Brain-computer interfaces and virtual reality for neurorehabilitation
    15. Monitoring performance of professional and occupational operators
    16. Self-Health Monitoring and wearable neurotechnologies
    17. Brain-computer interfaces for basic neuroscience
    18. Electroencephalography
    19. iEEG: dura-lining electrodes
    20. Local field potentials for BCI control
    21. Real-time fMRI for brain-computer interfacing
    22. Merging brain-computer interface and functional electrical stimulation technologies for movement restoration
    23. General principles of machine learning for brain-computer interfacing
    24. Ethics and the emergence of brain-computer interface medicine
    25. Industrial perspectives on brain computer interface technology
    26. Hearing the needs of clinical users

Product details

  • No. of pages: 390
  • Language: English
  • Copyright: © Elsevier 2020
  • Published: March 10, 2020
  • Imprint: Elsevier
  • Hardcover ISBN: 9780444639349
  • eBook ISBN: 9780444639332

About the Series Volume Editors

Nick F. Ramsey

Nick Ramsey has a degree in Psychology and a PhD in neuro-psychopharmacology, both from the university of Utrecht (Netherlands). He became a specialist in cognitive neuroimaging in the US (National Institutes of Health), and applies modern techniques, including fMRI and intracranial EEG, to questions on working memory, language, and sensorimotor function. His primary goal is to acquire and translate neuro-scientific insights to patients with neurological and psychiatric disorders, with a focus on brain-computer interfacing. He is full professor in cognitive neuroscience at the department of neurology and neurosurgery of the UMC Utrecht since 2007. He has been awarded several personal grants including a VIDI (NWO, 2002) for elucidating working memory, a VICI (NWO, 2006) and later a European ERC Advanced grant for developing intracranial BCI concepts for paralyzed people. The BCI research resulted in an implantable prototype for locked-in patients the first of who has now been using the implant for over 3 years for communication. He also was awarded several Valorisation grants and started a spin-off company to provide Clinical fMRI reports to clinicians. He has supervised over 20 PhD students and has (co)authored over 190 peer-reviewed publications.

Affiliations and Expertise

Professor in Cognitive Neuroscience, Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, University Medical Center Utrecht, The Netherlands

José del R. Millán

José del R. Millán is with the Dept. of Electrical & Computer Engineering and in the Dept. of Neurology of the University of Texas at Austin since September 2019, where he holds the Motorola Regents Chair in Electrical and Computer Engineering #2. Dr. Millán held the Defitech Foundation Chair at the École Polytechnique Fédérale de Lausanne (EPFL) from 2009 to 2019, where he helped establish the Center for Neuroprosthetics. He received a PhD in computer science from the Technical University of Catalonia, Barcelona, in 1992. Dr. Millán has made several seminal contributions to the field of brain-computer interfaces (BCI), especially based on electroencephalogram (EEG) signals. Most of his achievements revolve around the design of brain-controlled robots. He has received several recognitions for these seminal and pioneering achievements, notably the IEEE-SMC Nobert Wiener Award in 2011 and elevation to IEEE Fellow in 2017. In addition to his work on the fundamentals of BCI and design of neuroprosthetics, Dr. Millán is prioritizing the translation of BCI to end-users suffering from motor and cognitive disabilities. In parallel, he is designing BCI technology to offer new interaction modalities for able-bodied people.

Affiliations and Expertise

Carol Cockrell Curran Endowed Chair, Department of Electrical and Computer Engineering and Department of Neurology, The University of Texas at Austin, USA

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