Analysis and Classification of EEG Signals for Brain-Computer Interfaces

1. Auflage 2020
ISBN: 978-3-030-30580-2
Verlag: Springer International Publishing

Buch, Englisch, Band 852, 132 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 383 g

Reihe: Studies in Computational Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Paszkiel, Szczepan

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion

Inhaltsverzeichnis

Chapter 1. Introduction.- Chapter 2. Data acquisition methods for human brain activity.- Chapter 3. Brain-computer interface (BCI) technology, etc.