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Punto di Riferimento
per Medici e Operatori Sanitari
per Medici e Operatori Sanitari
LIBRERIA STUDIUM
EEG-Based Diagnosis of Alzheimer Disease
A Review and Novel Approaches for Feature Extraction and Classification Techniques
Kulkarni, Bairagi
Editore
Elsevier
Anno
2018
Pagine
110
ISBN
9780128153925
105,00 €
DA SCONTARE
Features:
- Includes the mathematical models and rigorous analysis of various classifiers and machine learning algorithms from a perspective of clinical deployment
- Covers the history of EEG signals and their measurement and recording, along with their uses in clinical diagnostics
- Analyzes spectral, wavelet, complexity and other features of early and efficient Alzheimer’s Disease diagnostics
- Explores support vector machine-based classification to increase accuracy
Chapter 1: Introduction
1.1 What is Alzheimer’s Disease?
1.2 Causes and Symptoms of the disease
1.3 Stages and Clinical Diagnosis of the 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 of Alzheimer disease
1.5.1 Role of Neuroimaging based techniques in diagnosis of Alzheimer disease
1.5.2 Role of Electroencephalogram techniques in diagnosis of Alzheimer disease
1.6 Summary
Chapter 2: Electroencephalogram and Its Use in Clinical Neuroscience
2.1 Introduction
2.2 EEG Recording techniques and Measurement
2.3 EEG Rhythms and their significance
2.4 Early Diagnosis of Alzheimer disease using EEG signals
2.5 Summary
Chapter 3: Role of Different Features in Diagnosis of Alzheimer’s Disease
3.1 Introduction
3.2 What is Feature extraction?
3.3 Need of Feature Extraction in EEG signals
3.4 Linear Features
3.4.1 Spectral Features
3.4.2 Wavelet Based Features
3.5 Non-Linear Features
3.5.1 Role of Complexity based features
3.5.2 Synchrony based features
Chapter 4: Use of Complexity-Based Features in the Diagnosis of Alzheimer’s Disease
Chapter 5: Classification Algorithms in the Diagnosis of Alzheimer’s Disease
Chapter 6: Discussion and Research Challenges
