Smart Biosensing Technologies for Early Detection of Metabolic Disorders gives a clear overview of the latest biosensor tools that help detect and monitor metabolic diseases like diabetes, obesity, and insulin resistance early. It explains how these sensors work using basic science and shows new wearable, non-invasive, and easy-to-use devices. This book is useful for researchers, doctors, and professionals working in healthcare technology. This book connects research from different fields to help solve real problems in making and using biosensors. It includes examples of how these sensors are used, new markers for disease detection, and how AI and digital health can improve care. Readers will learn how to develop better diagnostic tools and improve treatment for metabolic diseases.
1. 1 Introduction - p. 109 2. 2 Evolution and current landscape of nanomaterial-based metabolic biosensing - p. 110 3. 3 Classification of nanomaterials for metabolic biosensing - p. 111 4. 4 Physicochemical properties governing biosensing performance - p. 120 5. 5 Nano–biomolecule interactions: Biophysical principles and models - p. 123 6. 6 Nanomaterial-enabled signal transduction, readout, and performance limitations in biosensors - p. 130 7. 7 Design strategies for sensitivity, selectivity, and system-level performance optimization - p. 135 8. 8 Characterization methods for nanomaterial-based biosensors - p. 139 9. 9 Analytical performance evaluation and regulatory validation of nanomaterial-based biosensors in complex biological matrices - p. 144 10. 10 Biocompatibility, immunological safety, and environmental fate of nanomaterial-based biosensors - p. 147 11. 11 Industrial translation of nanomaterial biosensors: Manufacturing scale-up, quality control, and commercialization pathways - p. 149 12. 12 Device integration and system-level engineering for nanomaterial-based biosensors - p. 151 13. 13 Practical biosensor design workflow: Decision framework, selection rules, and design templates - p. 153 14. 14 Open challenges and future directions in nanomaterial-based biosensing: A translational roadmap - p. 158 15. 15 Conclusion - p. 161 16. Chapter 5. Microfluidic and paper-based biosensing technologies for metabolic disorders: From sample processing to clinical translation - p. 171 17. Chapter 6. Wearable optical and electrochemical biosensors for continuous metabolic monitoring: Principles, system integration, and clinical translation - p. 217 18. Section III. Smart and intelligent biosensing approaches - p. S3 19. Chapter 7. Artificial intelligence and machine learning for metabolic biosensors: From data analytics to clinical deployment - p. 265 20. Chapter 8. Cloud–edge architectures for connected metabolic care: IoMT integration, interoperability, analytics, and lifecycle management - p. 305 21. Chapter 9. Continuous wearable and implantable biosensors for metabolic disorders: From biosensing technologies to clinical translation - p. 353 22. Section IV. Applications in early detection of specific metabolic disorders - p. S4 23. Chapter 10. Smart biosensing technologies for diabetes mellitus: From biomarker discovery and sensor design to clinical validation and real-world deployment - p. 401 24. Chapter 11. Multimodal biosensing and continuous phenotyping for obesity and metabolic syndrome: Biomarkers, sensor systems, and clinical translation - p. 463 25. Chapter 12. Translational cardiometabolic biosensing integrating biomarkers, multiplex panels, sensing strategies, and clinical validation - p. 519 26. 1 Introduction - p. 519 27. 2 Taxonomy of cardiometabolic biomarkers - p. 520 28. 3 Biological matrices, sampling strategies, and preanalytical considerations for cardiometabolic biosensing - p. 523 29. 4 Assay formats and affinity elements tailored to cardiometabolic targets - p. 527 30. 5 Transduction modalities applied to cardiometabolic biomarkers - p. 530 31. 6 Surface chemistry, anti-fouling, and matrix interference control - p. 533 32. 7 Multiplexing strategies and biomarker panel development for cardiometabolic biosensing - p. 538 33. 8 Analytical performance requirements and validation strategies for cardiometabolic biosensors - p. 540 34. 9 Clinical applications of POC and near-patient cardiometabolic biosensing - p. 544 35. 10 Continuous and wearable sensing prospects for cardiometabolic biomarkers - p. 548 36. 11 Data integrity, signal processing, and clinical interpretation for cardiometabolic biosensing - p. 553 37. 12 Clinical validation and evidence-generation pathways for cardiometabolic biosensors - p. 557 38. 13 Translational insights from representative cardiometabolic biosensor platforms - p. 560 39. 14 Technical challenges and future research priorities in cardiometabolic biosensing - p. 562 40. 15 Practical design and development guidelines for cardiometabolic biosensors - p. 565 41. 16 Conclusion - p. 568 42. Chapter 13. Multi-omic biomarkers, biosensing technologies, and precision diagnostics for rare and inherited metabolic disorders - p. 575 43. Chapter 14. Advanced biophysical biosensing strategies for monitoring oxidative stress and inflammation in metabolic disorders - p. 625 44. Section V. Translational perspectives and future directions - p. S5 45. Chapter 15. Translating smart biosensors for metabolic health: Regulatory pathways, ethical governance and commercialization strategy - p. 671 46. Index - p. 721
Smart Biosensing Technologies for Early Detection of Metabolic Disorders gives a clear overview of the latest biosensor tools that help detect and monitor metabolic diseases like diabetes, obesity, and insulin resistance early. It explains how these sensors work using basic science and shows new wearable, non-invasive, and easy-to-use devices. This book is useful for researchers, doctors, and professionals working in healthcare technology. This book connects research from different fields to help solve real problems in making and using biosensors. It includes examples of how these sensors are used, new markers for disease detection, and how AI and digital health can improve care. Readers will learn how to develop better diagnostic tools and improve treatment for metabolic diseases.
1. 1 Introduction - p. 109 2. 2 Evolution and current landscape of nanomaterial-based metabolic biosensing - p. 110 3. 3 Classification of nanomaterials for metabolic biosensing - p. 111 4. 4 Physicochemical properties governing biosensing performance - p. 120 5. 5 Nano–biomolecule interactions: Biophysical principles and models - p. 123 6. 6 Nanomaterial-enabled signal transduction, readout, and performance limitations in biosensors - p. 130 7. 7 Design strategies for sensitivity, selectivity, and system-level performance optimization - p. 135 8. 8 Characterization methods for nanomaterial-based biosensors - p. 139 9. 9 Analytical performance evaluation and regulatory validation of nanomaterial-based biosensors in complex biological matrices - p. 144 10. 10 Biocompatibility, immunological safety, and environmental fate of nanomaterial-based biosensors - p. 147 11. 11 Industrial translation of nanomaterial biosensors: Manufacturing scale-up, quality control, and commercialization pathways - p. 149 12. 12 Device integration and system-level engineering for nanomaterial-based biosensors - p. 151 13. 13 Practical biosensor design workflow: Decision framework, selection rules, and design templates - p. 153 14. 14 Open challenges and future directions in nanomaterial-based biosensing: A translational roadmap - p. 158 15. 15 Conclusion - p. 161 16. Chapter 5. Microfluidic and paper-based biosensing technologies for metabolic disorders: From sample processing to clinical translation - p. 171 17. Chapter 6. Wearable optical and electrochemical biosensors for continuous metabolic monitoring: Principles, system integration, and clinical translation - p. 217 18. Section III. Smart and intelligent biosensing approaches - p. S3 19. Chapter 7. Artificial intelligence and machine learning for metabolic biosensors: From data analytics to clinical deployment - p. 265 20. Chapter 8. Cloud–edge architectures for connected metabolic care: IoMT integration, interoperability, analytics, and lifecycle management - p. 305 21. Chapter 9. Continuous wearable and implantable biosensors for metabolic disorders: From biosensing technologies to clinical translation - p. 353 22. Section IV. Applications in early detection of specific metabolic disorders - p. S4 23. Chapter 10. Smart biosensing technologies for diabetes mellitus: From biomarker discovery and sensor design to clinical validation and real-world deployment - p. 401 24. Chapter 11. Multimodal biosensing and continuous phenotyping for obesity and metabolic syndrome: Biomarkers, sensor systems, and clinical translation - p. 463 25. Chapter 12. Translational cardiometabolic biosensing integrating biomarkers, multiplex panels, sensing strategies, and clinical validation - p. 519 26. 1 Introduction - p. 519 27. 2 Taxonomy of cardiometabolic biomarkers - p. 520 28. 3 Biological matrices, sampling strategies, and preanalytical considerations for cardiometabolic biosensing - p. 523 29. 4 Assay formats and affinity elements tailored to cardiometabolic targets - p. 527 30. 5 Transduction modalities applied to cardiometabolic biomarkers - p. 530 31. 6 Surface chemistry, anti-fouling, and matrix interference control - p. 533 32. 7 Multiplexing strategies and biomarker panel development for cardiometabolic biosensing - p. 538 33. 8 Analytical performance requirements and validation strategies for cardiometabolic biosensors - p. 540 34. 9 Clinical applications of POC and near-patient cardiometabolic biosensing - p. 544 35. 10 Continuous and wearable sensing prospects for cardiometabolic biomarkers - p. 548 36. 11 Data integrity, signal processing, and clinical interpretation for cardiometabolic biosensing - p. 553 37. 12 Clinical validation and evidence-generation pathways for cardiometabolic biosensors - p. 557 38. 13 Translational insights from representative cardiometabolic biosensor platforms - p. 560 39. 14 Technical challenges and future research priorities in cardiometabolic biosensing - p. 562 40. 15 Practical design and development guidelines for cardiometabolic biosensors - p. 565 41. 16 Conclusion - p. 568 42. Chapter 13. Multi-omic biomarkers, biosensing technologies, and precision diagnostics for rare and inherited metabolic disorders - p. 575 43. Chapter 14. Advanced biophysical biosensing strategies for monitoring oxidative stress and inflammation in metabolic disorders - p. 625 44. Section V. Translational perspectives and future directions - p. S5 45. Chapter 15. Translating smart biosensors for metabolic health: Regulatory pathways, ethical governance and commercialization strategy - p. 671 46. Index - p. 721
