Emerging Diagnostic Glucose Sensing Approaches: Diabetes
Editat de Abhishek Kandwal, Nie Zedong, Rohit Jasrotiaen Limba Engleză Paperback – iun 2026
Measuring blood glucose levels using electromagnetic waves is now one of the most prominent candidates fulfilling the criteria for blood glucose monitoring. In addition, research using Physiological techniques (ECG and EEG) that integrate artificial intelligence/deep learning are making new breakthroughs. Success in this research requires the applications of physical models for accurate analytical studies, the use of biomedical methodologies for understanding the human body phenomena, and the application of engineering tools for the development of the prototypes.
- Provides 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 for desired applications
- Offers a multidisciplinary review on new sensing methods to explore research analysis in the field of diabetes
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Specificații
ISBN-13: 9780443363481
ISBN-10: 044336348X
Pagini: 500
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 044336348X
Pagini: 500
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
Cuprins
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
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