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Analysis and Classification of EEG Signals for Brain–Computer Interfaces / / by Szczepan Paszkiel



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Autore: Paszkiel Szczepan Visualizza persona
Titolo: Analysis and Classification of EEG Signals for Brain–Computer Interfaces / / by Szczepan Paszkiel Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Edizione: 1st ed. 2020.
Descrizione fisica: 1 online resource (VI, 132 p.)
Disciplina: 003.5
612.80285
Soggetto topico: Computational intelligence
Biomedical engineering
Neurobiology
Artificial intelligence
Computational Intelligence
Biomedical Engineering and Bioengineering
Artificial Intelligence
Nota di contenuto: Chapter 1. Introduction -- Chapter 2. Data acquisition methods for human brain activity -- Chapter 3. Brain-computer interface (BCI) technology, etc.
Sommario/riassunto: 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.
Titolo autorizzato: Analysis and Classification of EEG Signals for Brain–Computer Interfaces  Visualizza cluster
ISBN: 3-030-30581-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484074603321
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Serie: Studies in Computational Intelligence, . 1860-949X ; ; 852