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.
1. Chapter 1 Introduction to neurodegenerative disorders: Unraveling the complex interplay of cognitive decline - p. 1 2. Chapter 2 Introduction to machine learning and deep learning for neurodegenerative diseases assessment - p. 31 3. Chapter 3 The mechanics of the movement - p. 73 4. Chapter 4 Wearable sensors for neurodegenerative disease assessment - p. 91 5. Chapter 5 A review of noninvasive sensors and techniques for detecting the early sign of neurodegenerative disease using machine learning - p. 103 6. Chapter 6 Smartphone-based detection of neurodegenerative disease - p. 125 7. Chapter 7 Impact of data generation on performance and explainability of speech-based Parkinson’s detection models - p. 135 8. Chapter 8 Identifying emotion patterns in speech for Alzheimer’s disease assessment: A novel perspective - p. 147 9. Chapter 9 Detection of early signs of neurodegenerative disease through digital tablets and handwriting - p. 187 10. Chapter 10 Computer vision methods for neuroimaging based detection and monitoring of neurodegenerative disorders neurodegenerative diseases through neuroimaging techniques - p. 203 11. Chapter 11 Development of Internet of Things Fresh Quality Model (IoT-FQM): A quality model for Internet of Things healthcare - p. 221 12. Chapter 12 Explainable techniques for trustworthy artificial intelligence - p. 275 13. Chapter 13 Handling missing data in the assessment of neurodegenerative diseases - p. 311 14. Chapter 14 Conclusions and future research directions - p. 333 15. Index - p. 349
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.
1. Chapter 1 Introduction to neurodegenerative disorders: Unraveling the complex interplay of cognitive decline - p. 1 2. Chapter 2 Introduction to machine learning and deep learning for neurodegenerative diseases assessment - p. 31 3. Chapter 3 The mechanics of the movement - p. 73 4. Chapter 4 Wearable sensors for neurodegenerative disease assessment - p. 91 5. Chapter 5 A review of noninvasive sensors and techniques for detecting the early sign of neurodegenerative disease using machine learning - p. 103 6. Chapter 6 Smartphone-based detection of neurodegenerative disease - p. 125 7. Chapter 7 Impact of data generation on performance and explainability of speech-based Parkinson’s detection models - p. 135 8. Chapter 8 Identifying emotion patterns in speech for Alzheimer’s disease assessment: A novel perspective - p. 147 9. Chapter 9 Detection of early signs of neurodegenerative disease through digital tablets and handwriting - p. 187 10. Chapter 10 Computer vision methods for neuroimaging based detection and monitoring of neurodegenerative disorders neurodegenerative diseases through neuroimaging techniques - p. 203 11. Chapter 11 Development of Internet of Things Fresh Quality Model (IoT-FQM): A quality model for Internet of Things healthcare - p. 221 12. Chapter 12 Explainable techniques for trustworthy artificial intelligence - p. 275 13. Chapter 13 Handling missing data in the assessment of neurodegenerative diseases - p. 311 14. Chapter 14 Conclusions and future research directions - p. 333 15. Index - p. 349
