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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Dedication - p. v 7. Contributors - p. xiii 8. Editors - p. xvii 9. Preface - p. xix 10. 1. Diabetes, glucose sensing, requirements, challenges, and techniques - p. 1 11. 2. Current progress in RF sensing for glucose monitoring - p. 29 12. 3. Electromagnetic wave sensors: Design, fabrication, and development - p. 47 13. 4. In vitro and In vivo testing methods - p. 67 14. 5. Physiological technique for glucose estimation: Methods, applications, and advantages - p. 85 15. 6. Prediction of prediabetes: Artificial neural networking - p. 105 16. 7. Spatiotemporal feature extraction and analysis of ECG and EEG signals for glucose monitoring - p. 125 17. 8. Bioimpedance-based approach - p. 141 18. 9. Portable and noninvasive blood glucose monitoring - p. 163 19. 10. Roles of surface waves and Goubau lines - p. 185 20. 11. Colorimetric sensing platforms for noninvasive glucose monitoring - p. 209 21. 12. Photoplethysmography (PPG) based noninvasive blood glucose monitoring - p. 229 22. 13. Sensing and control: Future and vision - p. 247 23. Index - p. 261
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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Dedication - p. v 7. Contributors - p. xiii 8. Editors - p. xvii 9. Preface - p. xix 10. 1. Diabetes, glucose sensing, requirements, challenges, and techniques - p. 1 11. 2. Current progress in RF sensing for glucose monitoring - p. 29 12. 3. Electromagnetic wave sensors: Design, fabrication, and development - p. 47 13. 4. In vitro and In vivo testing methods - p. 67 14. 5. Physiological technique for glucose estimation: Methods, applications, and advantages - p. 85 15. 6. Prediction of prediabetes: Artificial neural networking - p. 105 16. 7. Spatiotemporal feature extraction and analysis of ECG and EEG signals for glucose monitoring - p. 125 17. 8. Bioimpedance-based approach - p. 141 18. 9. Portable and noninvasive blood glucose monitoring - p. 163 19. 10. Roles of surface waves and Goubau lines - p. 185 20. 11. Colorimetric sensing platforms for noninvasive glucose monitoring - p. 209 21. 12. Photoplethysmography (PPG) based noninvasive blood glucose monitoring - p. 229 22. 13. Sensing and control: Future and vision - p. 247 23. Index - p. 261
