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OverviewThis book introduces signal processing and machine learning techniques for BMI/BCI and outline their practical and future applications in neuroscience, medicine, and rehabilitation, with a focus on EEG-based BMI/BCI methods and technologies. Full Product DetailsAuthor: Toshihisa Tanaka (Associate Professor, Tokyo University of Agriculture and Technology, Department of Electrical and Electronic Engineering, Japan) , Mahnaz Arvaneh (Lecturer, University of Sheffield, UK)Publisher: Institution of Engineering and Technology Imprint: Institution of Engineering and Technology ISBN: 9781785613982ISBN 10: 1785613987 Pages: 360 Publication Date: 18 November 2018 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsChapter 1: Brain-computer interfaces and electroencephalogram: basics and practical issues Chapter 2: Discriminative learning of connectivity pattern of motor imagery EEG Chapter 3: An experimental study to compare CSP and TSM techniques to extract features during motor imagery tasks Chapter 4: Robust EEG signal processing with signal structures Chapter 5: A review on transfer learning approaches in brain-computer interface Chapter 6: Unsupervised learning for brain-computer interfaces based on event-related potentials Chapter 7: Covariate shift detection-based nonstationary adaptation in motor-imagery-based brain-computer interface Chapter 8: A BCI challenge for the signal-processing community: considering the user in the loop Chapter 9: Feedforward artificial neural networks for event-related potential detection Chapter 10: Signal models for brain interfaces based on evoked response potential in EEG Chapter 11: Spatial filtering techniques for improving individual template-based SSVEP detection Chapter 12: A review of feature extraction and classification algorithms for image RSVP-based BCI Chapter 13: Decoding music perception and imagination using deep-learning techniques Chapter 14: Neurofeedback games using EEG-based brain-computer interface technologyReviewsAuthor InformationToshihisa Tanaka is an Associate Professor at the Department of Electrical and Electronic Engineering of Tokyo University of Agriculture and Technology. He is Co-editor of Signal Processing Techniques for Knowledge Extraction and Information Fusion, and Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, Computational Intelligence and Neuroscience, and Advances in Data Science and Adaptive Analysis. He is also a member-at-large of the board of governors of Asia-Pacific Signal and Information Processing Association (APSIPA), a senior member of the IEEE, and a member of the IEICE and APSIPA. Mahnaz Arvaneh is a Lecturer in the Department of Automatic Control and Systems Engineering and a member of Centre for Assistive Technology and Connected Health (CATCH) at the University of Sheffield, UK. She is an Associate Editor in IEEE Transaction on Neural Systems and Rehabilitation Engineering, as well as a technical committee member for APSIPA and the IEEE Systems, Man, Cybernetics conference. Through her research, she aims to improve our understanding of the human body, both to address fundamental questions in the control of physiological systems and to develop improved therapeutic, assistive, adaptive and rehabilitative technologies for a variety of medical conditions. Tab Content 6Author Website:Countries AvailableAll regions |
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