The book extensively explores Brain-Computer Interfaces (BCIs), emphasizing both the theoretical foundations and practical applications within this rapidly advancing field. It provides a thorough coverage of BCI fundamentals and practical implementation using MATLAB (R). It begins with an introduction, covering the history of BCIs, components, and the pivotal role MATLAB (R) plays in their development. The book explores various aspects such as signal processing, data acquisition, rapid prototyping, machine learning, and real-time data processing, all within the MATLAB (R) environment. Additionally, it delves into the community and support available, along with open-source BCI toolboxes and integration with external devices. Moving forward, the book dives into the fundamentals of BCIs, including their definition, applications, principles, and components. It covers different types of brain signals utilized in BCI systems and the challenges involved in their design, such as signal reliability, userfriendliness, privacy, and regulatory issues. It discusses their principles, implementation in MATLAB (R), and practical considerations for training and evaluating classification models. Finally, the book concludes with real-world case studies and practical examples, demonstrating the application of MATLAB (R) in BCI projects.
This book is an essential reading for researchers, engineers, students, and practitioners seeking to explore the fascinating intersection of neuroscience, signal processing, and machine learning through MATLAB-based BCI development.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic and Postgraduate
Illustrationen
27 s/w Abbildungen, 15 farbige Abbildungen, 1 s/w Photographie bzw. Rasterbild, 2 Farbfotos bzw. farbige Rasterbilder, 26 s/w Zeichnungen, 13 farbige Zeichnungen
13 Line drawings, color; 26 Line drawings, black and white; 2 Halftones, color; 1 Halftones, black and white; 15 Illustrations, color; 27 Illustrations, black and white
Maße
Höhe: 260 mm
Breite: 183 mm
Dicke: 14 mm
Gewicht
ISBN-13
978-1-032-95154-6 (9781032951546)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Faridoddin Shariaty is a distinguished researcher in Artificial Intelligence applications in medicine, specializing in Medical Image Processing. He is currently a Research Assistant at Peter the Great St Petersburg Polytechnic University in St Petersburg, Russia. He is involved in pioneering research in computer-aided diagnosis systems, leveraging advanced machine learning techniques to enhance medical diagnostics.
Sanjiban Sekhar Roy is a Professor in the School of Computer Science and Engineering, Vellore Institute of Technology. He has a PhD from Vellore Institute of Technology (2016). His research interests include deep learning and advanced machine learning. Dr. Roy is a recipient of the "Diploma of Excellence" award for academic research in the year 2019 from the Ministry of National Education, Romania. He was an associate researcher in Ton Duc Thang University, Vietnam (2019-20). He has served as an editor of a handful of special issues for journals, published numerous articles in SCI high impact journals and many books with reputed publishers.
Autor*in
Peter the Great St. Petersburg Polytechnic University St. Petersburg, Russia
Preface. An Introduction to Brain-Computer Interface Systems. Fundamentals of Brain-Computer Interfaces. Introduction to MATLAB (R) for BCI Systems. Signal Acquisition and Preprocessing. Feature Extraction and Representation. Classification Algorithms for BCI Systems. Case Studies and Practical Examples. Conclusion. Appendix A MATLAB (R) Code Snippets. Index.
