Brain-computer interfacing for assistive robotics: electroencephalograms, recurrent quantum neural networks and user-centric graphical user interfaces

Gandhi, Vaibhav (2014) Brain-computer interfacing for assistive robotics: electroencephalograms, recurrent quantum neural networks and user-centric graphical user interfaces. Elsevier.

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Abstract

Brain-computer interface (BCI) technology provides a means of communication that allows individuals with severely impaired movement to communicate with assistive devices using the electroencephalogram (EEG) or other brain signals. The practicality of a BCI has been possible due to advances in cognitive neuroscience, brain-imaging, and human-computer interfaces. Two major challenges remain in making BCI for assistive robotics practical for day-to-day use: the inherent lower bandwidth, and how to best handle unknown embedded noise within the raw EEG.

Brain-Computer Interfacing for Assistive Robotics is the first comprehensive
book covering both the theoretical and practical aspects of BCI for real-time
assistive robotive application. It covers the fundamental biological aspects of EEG before introducing and critically reviewing the various components of a typical BCI system. It details the fundamental issues related to non-stationary EEG signal processing (filtering) and the need for an alternative approach. Additionally, the book also discusses techniques for overcoming lower bandwidth of BCIs by designing novel use-centric graphical user interfaces. A detailed investigation into these approaches is discussed along with real-time practical experiments and author-provided video demonstration links hosted via a companion website.

Key features:
• An innovative reference on the components of the BCI system and its utility in computational neuroscience and real-time assistive robotics
• Written for researchers, students, and computational neuroscientists,
provides a novel guide to the fundamentals of quantum mechanics for
BCI and the Schrodinger Wave equation in designing, understanding, and
implementing the Recurrent Quantum Neural Network (RQNN)
• Full-color text detailing the fundamental issues related with signal processing and the need for alternative approaches
• Overview of intelligent adaptive user interface (iAUI) within the complete BCI
system, and details the practical implementation of the RQNN and the iAUI in MATLAB/Simulink and Visual Basic for real-time robot control through video links of recorded live robot control by the user’s imagination.

Item Type: Book
Keywords (uncontrolled): Brain-Computer Interface, Assistive Robotics, Quantum Neural Network, EEG, Signal Processing
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 16381
Notes on copyright: Access to full text restricted pending copyright check.
Useful Links:
Depositing User: Vaibhav Gandhi
Date Deposited: 28 May 2015 10:53
Last Modified: 04 May 2019 04:39
URI: https://eprints.mdx.ac.uk/id/eprint/16381

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