Full Description
Emerging Diagnostic Glucose Sensing Approaches surveys past and recent work on non-invasive blood glucose monitoring. The book highlights two complementary paths: electromagnetic-wave-based sensing, using physical models and advanced sensors to measure glucose non-invasively; and physiological techniques (ECG/EEG) integrated with artificial intelligence and deep learning to infer glucose levels. It discusses how physical models, biomedical methodologies, and engineering prototyping enable accurate analysis and device development. With a focus on breakthroughs in electromagnetic sensors and non-invasive research, this volume serves as a foundational reference for biomedical researchers and engineers pursuing next-generation glucose monitoring.
Contents
1. Diabetes, Glucose sensing, Requirements, Challenges and Techniques
2. Current Progress in RF sensing for Glucose monitoring
3. Electromagnetics wave Sensors: Design, Fabrication, and Development
4. Testing methods: Invitro and Invivo
5. Physiological Technique: Method, Need and Advantages
6. Prediction of prediabetes: Artificial neural networking
7. Spatiotemporal ECG and EEG feature analysis
8. Bioimpedance based approach
9. Convolutional neural networking: Mult segments fusion and Varied weight
10. Portable and noninvasive blood glucose monitoring
11. Role of Surface waves and Goubau line
12. Statistical and spectral analysis of ECG signal
13. Deep learning intervention for health care challenges
14. Sensing and control: Future and Vision
