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Diabetes is a major global health concern affecting millions worldwide, where frequent blood glucose monitoring is critical to prevent further complications. The development of point-of-care self-monitoring of blood glucose (SMBG) devices revolutionized diabetes management. However, limitations, including their invasive nature and isolated glucose level determination, led to the development of continuous glucose monitoring (CGM) devices. The use of minimally invasive sensors and a longer period of measurement contributes to higher adherence in diabetes patients, which further leads to better glycaemic performances. This chapter describes the evolution of CGM devices as a case study for continuous monitoring of diabetes, the sensing mechanism of the devices, and the electronic components for real-time data acquisition and transmission. A comparison of different commercially available CGMs is discussed here. Finally, this chapter addresses the future of CGM and highlights the potential of artificial intelligence and machine learning in these systems. These advancements make CGM a breakthrough in diabetes care and a model system for personalized medicine.

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Development of Continuous Glucose Monitoring Systems for Better Diabetes Management

  • 章节

  • 发表日期：

    2026年

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  • Sushant Sharma,
  • Rohit Mohite,
  • Paras J. Keyravan,
  • Archita Jha,
  • Kishor Deshmukh,
  • Dilnawaz Ansari,
  • Hussain Valikarimwala,
  • Amey Khatavkar,
  • Buddhadev Purohit,
  • Rohit Srivastava

摘要

Diabetes is a major global health concern affecting millions worldwide, where frequent blood glucose monitoring is critical to prevent further complications. The development of point-of-care self-monitoring of blood glucose (SMBG) devices revolutionized diabetes management. However, limitations, including their invasive nature and isolated glucose level determination, led to the development of continuous glucose monitoring (CGM) devices. The use of minimally invasive sensors and a longer period of measurement contributes to higher adherence in diabetes patients, which further leads to better glycaemic performances. This chapter describes the evolution of CGM devices as a case study for continuous monitoring of diabetes, the sensing mechanism of the devices, and the electronic components for real-time data acquisition and transmission. A comparison of different commercially available CGMs is discussed here. Finally, this chapter addresses the future of CGM and highlights the potential of artificial intelligence and machine learning in these systems. These advancements make CGM a breakthrough in diabetes care and a model system for personalized medicine.