The Physics and Mathematics of Electroencephalogram
eBook - ePub

The Physics and Mathematics of Electroencephalogram

  1. 476 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

The Physics and Mathematics of Electroencephalogram

About this book

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.

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Yes, you can access The Physics and Mathematics of Electroencephalogram by Dezhong Yao in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Biomedical Science. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Endorsement Page
  3. Half Title
  4. Title Page
  5. Copyright Page
  6. Table of Contents
  7. Author
  8. Preface
  9. Introduction
  10. Chapter 1 Overview of EEG
  11. Chapter 2 Electromagnetics behind Brain Electric Field
  12. Chapter 3 Biophysics and Source Models of EEG
  13. Chapter 4 Brain Electrical Field in Regular Head Model
  14. Chapter 5 Brain Electrical Field in Realistic Head Model
  15. Chapter 6 Theory of Equivalent Distributed Sources
  16. Chapter 7 High-Resolution Cortical Imaging
  17. Chapter 8 Scalp Laplacian Imaging
  18. Chapter 9 A Unified Framework for High-Resolution EEG
  19. Chapter 10 Basic Theory of EEG Inverse Problem
  20. Chapter 11 Signal Space-Based EEG Inverse Solution
  21. Chapter 12 Iterative Minimum Norm Solution
  22. Chapter 13 Zero-Reference for Scalp EEG
  23. Chapter 14 EEG Reference Selection
  24. Chapter 15 EEG Cloud Platform – WeBrain
  25. Appendix A: δ Functions and Legendre Functions
  26. Appendix B: Analytical Potential Solutions for Regular Head Model
  27. Appendix C: Green Function, Green Integral, and Reciprocity Theorem
  28. Appendix D: Scalp Laplacian and Skull Surface Potential
  29. Appendix E: Mathematical Theory of Linear Inverse Problems
  30. Appendix F: Physics of EEG Average Reference
  31. Appendix G: Reference Electrode Problem in Mathematics
  32. Appendix H: Vector, Tensor, and Matrix
  33. Index