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Emerging Diagnostic Glucose Sensing Approaches

Diabetes

  • 1st Edition - June 1, 2026
  • Latest edition
  • Editors: Abhishek Kandwal, Nie Zedong, Rohit Jasrotia
  • Language: English

Emerging Diagnostic Glucose Sensing Approaches surveys past and recent work on non-invasive blood glucose monitoring. The book highlights two complementary paths: electr… Read more

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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.

Key features

  • Provides new methodologies on new diagnostic glucose sensing approaches as a part of industrial and societal applications
  • Includes the latest techniques required for simulating, designing, and testing on system level to utilize them for desired applications
  • Offers a multidisciplinary review on new sensing methods to explore research analysis in the field of diabetes

Readership

Anyone in the field of non-invasive blood glucose monitoring and new diagnostic research, researchers in biomedical, applied physics and electromagnetic fields, researchers working in the emerging field of diabetes and diagnostics

Table of 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

Product details

  • Edition: 1
  • Latest edition
  • Published: June 1, 2026
  • Language: English

About the editors

AK

Abhishek Kandwal

Abhishek Kandwal (Senior Member, IEEE) is presently working as an Associate Professor in the School of CHIPS at Xi'an Jiaotong Liverpool University and is Honorary Associate at University of Liverpool, UK. He is Listed in World Top 2% Scientist List of Stanford and Elsevier, 2025. Earlier, he received his Ph.D in Physics (Electromagnetic Waves) in 2014. He has over 14-years of research/teaching experience from some of the world top universities and research organizations. He has authored over 150-international research publications and filed/granted more than 10-national/international Patents. He served as Associate Editor for IEEE Access Journal (2019-22). Presently he is Associate Editor for Journal of King Saud University - Eng. Sci, Springer (2024-continue), special Issue Editor of various journals in Elsevier, Springer, Wiley (2023-continue), Editorial Board Member of Nature: Scientific Reports Journal (2024-continue), Editorial Board Member of Discover Materials and Discover Sensors, Springer (2024-continue)

Affiliations and expertise
, PhD, SMIEEE, is Associate Professor at School of CHIPS, Xi'an Jiaotong - Liverpool University, Suzhou, China and also Honorary Associate at Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, United Kingdom (UK)

NZ

Nie Zedong

Prof. Zedong Nie is Professor and Doctoral supervisor in the

Biomedical and Health Engineering department at Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (SIAT-CAS), China. Dr. Nie has expertise in human body communication and wearable health technology. His research interest includes noninvasive blood glucose monitoring, wearable sensors, communication system and protocol, biometric verification, and AI/machine learning. He's won several Research achievement awards, has applied for more than 60 invention patents and 7 PCT patents with 33 invention patents that have been authorized and more than 70 SCI/Scopus papers have been published. He is the evaluation expert of National Natural Science Foundation of China and Guangdong provincial science and technology department, and the reviewer of several reputed IEEE Journals. He won the honor of innovation and entrepreneurial talent of Shenzhen. He has several national level funding grants for Glucose monitoring and human body communications.

Affiliations and expertise
PhD, SMIEEE, is Professor and Doctoral Supervisor at Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences (SIAT-CAS), China

RJ

Rohit Jasrotia

Dr. Rohit Jasrotia is currently a Postdoctoral Fellow at the College of Chemistry and Molecular Science, Henan University, Kaifeng, Henan, PR China. He previously served as a Research Fellow and Assistant Professor at the Himalayan Centre of Excellence, Shoolini University, Solan, India. Dr. Jasrotia has published more than 135 research articles in reputed international journals, with over 4,100 citations and an h-index of 39. He has edited several scholarly books indexed in Elsevier databases and has been recognized among the Top 2% Scientists worldwide by Stanford University in collaboration with Elsevier. He has also served as a Special Issue Managing Editor for various journals published by Elsevier and Springer.

Affiliations and expertise
Post Doctoral Fellow, College of Chemistry and Molecular Science, Henan University, Kaifeng, Henan, China