Analysis and Classification of EEG Signals for Brain–Computer Interfaces

Analysis and Classification of EEG Signals for Brain–Computer Interfaces
Author :
Publisher : Springer Nature
Total Pages : 131
Release :
ISBN-10 : 9783030305819
ISBN-13 : 3030305813
Rating : 4/5 (813 Downloads)

Book Synopsis Analysis and Classification of EEG Signals for Brain–Computer Interfaces by : Szczepan Paszkiel

Download or read book Analysis and Classification of EEG Signals for Brain–Computer Interfaces written by Szczepan Paszkiel and published by Springer Nature. This book was released on 2019-08-31 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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