Development of a Fully Integrated Wearable System for Continuous Glucose and Vital Signs Monitoring /Mohammad Atef Ibrahim Mohammad Mansour
Material type:
TextLanguage: English Summary language: English Publication details: 2024Description: 180 p. ill. 21 cmSubject(s): Genre/Form: DDC classification: - 621
| Item type | Current library | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|
Thesis
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Main library | 621/M.A.D/ 2024 (Browse shelf(Opens below)) | Not for loan |
Supervisor: Ahmed Soltan
Thesis (M.A.)—Nile University, Egypt, 2024 .
"Includes bibliographical references"
Contents:
Table of Contents
Page
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IX
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . X
List of Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . XI
List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . XII
1. Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Development and Implementation Roadmap . . . . . . . . . . . . . . . . . . 2
1.4 Contributions Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.5 Thesis Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Wearable Devices for Continuous Glucose Monitoring 5
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Wearable biosensors role in bio-molecules sensing . . . . . . . . . . . . . . . 10
2.3 Glucose sensing principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.1 Classifications of glucose biosensors . . . . . . . . . . . . . . . . . . 13
2.3.2 Interstitial fluid (ISF) . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.3.3 Sweat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.4 Optical coherent tomography . . . . . . . . . . . . . . . . . . . . . . 20
2.3.5 Bioimpedance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4 CGM Electronic Components . . . . . . . . . . . . . . . . . . . . . . . . . . 21
IV
2.4.1 Analog Front End (AFE) . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.4.2 Microcontroller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4.3 Energy source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.5 Diabetes management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.5.1 Challenges of AI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.6 Commercial CGM systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.7 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.8 Discussion and future prospective . . . . . . . . . . . . . . . . . . . . . . . . 41
2.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3. Selection of IoT Protocols 45
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.1.1 Motivations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.1.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.1.3 Research Gaps and Contributions . . . . . . . . . . . . . . . . . . . . 47
3.1.4 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.2 IoT Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.2.1 IoT Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.2.2 The IoT Functional Building Elements . . . . . . . . . . . . . . . . . 50
3.3 The IoT Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.1 IoT Stack Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.3.2 Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.3.3 Edge and Fog Computing . . . . . . . . . . . . . . . . . . . . . . . . 53
3.4 IoT Application Layer Protocols . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.4.1 Message Queue Telemetry Transport (MQTT) . . . . . . . . . . . . . 55
3.4.2 Constrained Application Protocol (CoAP) . . . . . . . . . . . . . . . 55
3.4.3 Advanced Message Queuing Protocol (AMQP) . . . . . . . . . . . . . 56
3.4.4 HTTP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.4.5 Extensible Messaging and Presence Protocol (XMPP) . . . . . . . . . 56
3.5 IoT Communication Technologies . . . . . . . . . . . . . . . . . . . . . . . . 57
3.5.1 ZigBee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.5.2 BLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.5.3 Z-Wave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
V
3.5.4 Wi-Fi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.5.5 6LoWPAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.5.6 Wi-SUN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.5.7 LoRa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.5.8 LoRaWAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.5.9 NB-IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.5.10 Wired Communication Protocols . . . . . . . . . . . . . . . . . . . . 73
3.5.11 Hybrid Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.6 IoT Hardware Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
3.7 IoT Simulation Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.7.1 OpenDSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.7.2 NS-2/ NS-3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.7.3 OMNET++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.7.4 GridLab-D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.7.5 MATLAB/Simulink . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.7.6 GloMoSiM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.8 IoT Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
3.9 IoT Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.10 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
3.11 Low-Power Wireless protocol selection for continous glucose monitoring . . 87
3.11.1 Bluetooth Low Energy . . . . . . . . . . . . . . . . . . . . . . . . . . 88
3.11.2 Near Field Communication . . . . . . . . . . . . . . . . . . . . . . . 89
3.12 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4. System development and integration 91
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.2 System architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.2.1 Controller board . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.2.2 Sensor interface circuits . . . . . . . . . . . . . . . . . . . . . . . . . 97
4.3 Microneedle fabrication process . . . . . . . . . . . . . . . . . . . . . . . . . 98
4.4 Embedded software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.4.1 Micro-needle auto-calibration . . . . . . . . . . . . . . . . . . . . . . 100
4.4.2 Automatic Oxidation Peak Detector . . . . . . . . . . . . . . . . . . . 101
VI
4.4.3 Communications and System operation . . . . . . . . . . . . . . . . 103
4.4.4 Power Management . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
4.4.5 Detection of Hypo/Hyperglycemia . . . . . . . . . . . . . . . . . . . 106
4.4.6 Integration with Mobile Application . . . . . . . . . . . . . . . . . . 107
4.5 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
4.5.1 In-Vitro Characterization . . . . . . . . . . . . . . . . . . . . . . . . . 108
4.5.2 Readout Circuit Accuracy . . . . . . . . . . . . . . . . . . . . . . . . 109
4.5.3 Chronoamperometric Response Analysis and Calibration Algorithm
for Reduced Operation Time . . . . . . . . . . . . . . . . . . . . . . . 109
4.5.4 System integration and In-vivo testing . . . . . . . . . . . . . . . . . 112
4.5.5 Comparative Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 112
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5. Conclusions and Future Work 119
5.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
5.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Abstract:
The need for continuous, non-invasive glucose and vital signs monitoring has driven advancements in wearable technology, integrating biosensing, data transmission, and energyefficient designs. This thesis presents a comprehensive development of a fully integrated
wearable system for real-time glucose monitoring. The system employs microneedle technology for highly accurate glucose monitoring and Bluetooth Low Energy for efficient and
continuous data transmission. The glucose sensor, designed with electrochemical properties, facilitates accurate glucose detection through interstitial fluid with minimal invasiveness. Energy management is optimized with effective power reduction strategies, extending
the device’s operational lifespan and supporting prolonged wearability. Furthermore, the
system utilizes a robust communication framework, selecting BLE as an IoT protocol that
supports secure, real-time data transmission to a mobile interface. This connectivity facilitates remote monitoring, data logging, and alerts for hypoglycemia and hyperglycemia,
promoting a user-friendly and patient-centric design. By combining data from multiple vital
signs and applying predictive models, the system enhances precision health management,
allowing for more effective diabetes treatment and monitoring. The thesis highlights the
device’s practicality through comparative analyses, in vitro characterization, and in-vivo
testing, establishing its potential for broader adoption in healthcare.
Keywords: Continuous Glucose Monitoring, Glucose Wearable Sensors, Non-invasive
Glucose Monitoring, Health Monitoring, Precision Medicine.
Text in English, abstracts in English and Arabic
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