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EEG-based diagnosis of Alzheimer disease : a review and novel approaches for feature extraction and classification techniques /
EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book examines different...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Academic Press,
[2018]
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Intro; Title page; Table of Contents; Copyright; Dedication; Acknowledgments; Chapter One: Introduction; Abstract; 1.1. Alzheimer disease; 1.2. Causes and symptoms of the disease; 1.3. Stages and clinical diagnosis of Alzheimer's disease; 1.4. Importance of diagnosis of Alzheimer's disease and its impact on society; 1.5. A brief review on different methods used for diagnosis of Alzheimer disease; Summary; Chapter Two: Electroencephalogram and Its Use in Clinical Neuroscience; Abstract; 2.1. EEG recording and measurement; 2.2. EEG rhythms.
- 2.3. Early diagnosis of Alzheimer's disease by means of EEG signalsSummary; Chapter Three: Role of Different Features in Diagnosis of Alzheimer Disease; Abstract; 3.1. Introduction; 3.2. What is feature extraction?; 3.3. Need of feature extraction; 3.4. Linear features; 3.5. Conclusions; Chapter Four: Use of Complexity Features for Diagnosis of Alzheimer Disease; Abstract; 4.1. Introduction; 4.2. Use of new complexity features in Alzheimer's disease diagnosis; 4.3. Discussion and conclusion; Summary; Chapter Five: Classification Algorithms in Diagnosis of Alzheimer's Disease; Abstract.
- 5.1. IntroductionSummary; Chapter Six: Results, Discussions, and Research Challenges; Abstract; 6.1. Results; 6.2. Conclusions; 6.3. Contribution; 6.4. Limitations of the study; 6.5. Future scope; Index.