Behavioral Biometrics and Artificial Intelligence for Neurodegenerative Diseases Assessment
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Product details:
- Publisher Academic Press
- Date of Publication 11 May 2026
- ISBN 9780443135453
- Binding Paperback
- No. of pages300 pages
- Size 235x191 mm
- Language English 700
Categories
Long description:
Behavioral Biometrics and Artificial Intelligence for Neurodegenerative Diseases Assessment explores cutting-edge, non-invasive techniques for the early detection of neurodegenerative diseases. The book focuses on behavioral biometrics, which analyzes patterns in a person’s actions rather than directly measurable traits. By utilizing artificial intelligence methods-like machine learning and deep neural networks-it enables the observation of subtle changes in gait, handwriting, and speech. These advanced approaches offer promise for earlier and more accurate diagnosis, potentially improving outcomes for millions affected by conditions such as Alzheimer’s and Parkinson’s diseases through timely intervention and personalized care.
In addition to its core coverage, the book delves into the practical applications of wearable sensors and the use of everyday devices like smartphones and tablets in assessments. It provides comprehensive chapters on how these technologies can aid clinicians and researchers in monitoring disease progression outside traditional clinical settings.
- Presents motor patterns and the evolution of the most common neurodegenerative diseases
- Reviews most used behavioral biometrics for neurodegenerative disease assessment and how to measure them
- Outlines AI tools for neurodegenerative disease assessment
Table of Contents:
1. Introduction to neurodegenerative diseases
2. Machine learning
3. Feature extraction, feature selection, dimensionality reduction
4. Classification and Regression Models
5. Training and Testing by ensuring intrer-patient separation scheme
6. Model validation
7. Neural Networks
8. Deep Neural Networks for Computer Vision
9. Overview of modern architectures for image classification
10. Overview of modern architectures for time series classification
11. The mechanics of the movement
12. A review of noninvasive sensors and techniques for detecting the early sign of neurodegenerative disease using machine learning
13. Wearable sensors for Neurodegenerative disease assessment
14. Detection of early signs of neurodegenerative disease through smartphone app analyzing gait and five-time sit to stand tests
15. Detection of early signs of neurodegenerative disease through smartphones and speech audio
16. Detection of early signs of neurodegenerative disease through digital tablets and Handwriting
17. Computer Vision techniques for detecting neurodegenerative disease through neuroimaging techniques.
18. Explainable artificial intelligent techniques as a way to trust AI
19. Conclusions and future research directions
