Overview
- Presents a wealth of information on the development of brain–computer (BCI) technology with a particular focus on data acquisition methods and tools used for analyzing human brain activity
- Highlights recent research on the analysis and classification of EEG signals for brain–computer interfaces
- Covers research work on brain–computer technology, including identification of the sources of brain signals generated due to the correlation of neuronal cell fractions
Part of the book series: Studies in Computational Intelligence (SCI, volume 852)
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Table of contents (14 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book addresses the problem of EEG signal analysis and the need to classify it for practical use in many sample implementations of brain–computer interfaces. In addition, it offers a wealth of information, ranging from the description of data acquisition methods in the field of human brain work, to the use of Moore–Penrose pseudo inversion to reconstruct the EEG signal and the LORETA method to locate sources of EEG signal generation for the needs of BCI technology.
In turn, the book explores the use of neural networks for the classification of changes in the EEG signal based on facial expressions. Further topics touch on machine learning, deep learning, and neural networks. The book also includes dedicated implementation chapters on the use of brain–computer technology in the field of mobile robot control based on Python and the LabVIEW environment. In closing, it discusses the problem of the correlation between brain–computer technology and virtual reality technology.Authors and Affiliations
Bibliographic Information
Book Title: Analysis and Classification of EEG Signals for Brain–Computer Interfaces
Authors: Szczepan Paszkiel
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-30581-9
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-30580-2Published: 11 September 2019
Softcover ISBN: 978-3-030-30583-3Published: 11 September 2020
eBook ISBN: 978-3-030-30581-9Published: 31 August 2019
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: VI, 132
Topics: Computational Intelligence, Biomedical Engineering and Bioengineering, Neurobiology, Artificial Intelligence