The Physics and Mathematics of Electroencephalogram
Dezhong Yao
- 476 pagine
- English
- ePUB (disponibile sull'app)
- Disponibile solo in versione web
The Physics and Mathematics of Electroencephalogram
Dezhong Yao
Informazioni sul libro
This book focuses on a systematic introduction to the knowledge of mathematics and physics of electroencephalogram (EEG) and discusses an in-depth application of EEG and the development of new methods and technologies for mining and analyzing EEG.
The Physics and Mathematics of Electroencephalogram offers a systematic overview of the technology for brain function and disease. It covers six parts: background knowledge of EEG, EEG forward problems, high-resolution EEG imaging, EEG inverse problems, EEG reference electrode, and EEG cloud platform. The author reviews the critical technologies in brain function and disease, such as EEG sourcing, EEG imaging, and EEG reference electrode standardization technique. The book's aim is to clarify the mechanism of EEG from the perspective of physics, mathematics, and engineering science to help multidisciplinary readers better understand and use EEG information more effectively.
This book can be used as reference for researchers in the fields of neuroengineering, cognitive neuroscience, neurology, psychiatry, applied mathematics, and brain-like intelligence.
Domande frequenti
Informazioni
Indice dei contenuti
- Cover
- Endorsement Page
- Half Title
- Title Page
- Copyright Page
- Table of Contents
- Author
- Preface
- Introduction
- Chapter 1 Overview of EEG
- Chapter 2 Electromagnetics behind Brain Electric Field
- Chapter 3 Biophysics and Source Models of EEG
- Chapter 4 Brain Electrical Field in Regular Head Model
- Chapter 5 Brain Electrical Field in Realistic Head Model
- Chapter 6 Theory of Equivalent Distributed Sources
- Chapter 7 High-Resolution Cortical Imaging
- Chapter 8 Scalp Laplacian Imaging
- Chapter 9 A Unified Framework for High-Resolution EEG
- Chapter 10 Basic Theory of EEG Inverse Problem
- Chapter 11 Signal Space-Based EEG Inverse Solution
- Chapter 12 Iterative Minimum Norm Solution
- Chapter 13 Zero-Reference for Scalp EEG
- Chapter 14 EEG Reference Selection
- Chapter 15 EEG Cloud Platform – WeBrain
- Appendix A: δ Functions and Legendre Functions
- Appendix B: Analytical Potential Solutions for Regular Head Model
- Appendix C: Green Function, Green Integral, and Reciprocity Theorem
- Appendix D: Scalp Laplacian and Skull Surface Potential
- Appendix E: Mathematical Theory of Linear Inverse Problems
- Appendix F: Physics of EEG Average Reference
- Appendix G: Reference Electrode Problem in Mathematics
- Appendix H: Vector, Tensor, and Matrix
- Index