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

Book


Gandhi, V. 2014. Brain-computer interfacing for assistive robotics: electroencephalograms, recurrent quantum neural networks and user-centric graphical user interfaces. Elsevier.
TitleBrain-computer interfacing for assistive robotics: electroencephalograms, recurrent quantum neural networks and user-centric graphical user interfaces
AuthorsGandhi, V.
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.

KeywordsBrain-Computer Interface, Assistive Robotics, Quantum Neural Network, EEG, Signal Processing
LanguageEnglish
Edition1st
PublisherElsevier
Publication process dates
Deposited28 May 2015
Completed30 Sep 2014
Output statusPublished
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