REVIEW ARTICLE
Evaluation of Non-Invasive Wearable Diabetes Sensors
1
Faculty of Physics, Mathematics and Information Technologies, Department of Applied Informatics, Chechen State Pedagogical University, Russia
Submission date: 2024-06-02
Final revision date: 2024-06-28
Acceptance date: 2024-06-28
Publication date: 2024-06-30
Corresponding author
Piya Muradova
Faculty of Physics, Mathematics and Information Technologies, Department of Applied Informatics, Chechen State Pedagogical University, Russia
Faculty of Physics, Mathematics and Information Technologies, Department of Applied Informatics, Chechen State Pedagogical University, Russia
Sensors and Machine Learning Applications 2024;3(2)
KEYWORDS
TOPICS
ABSTRACT
Diabetes management has increasingly emphasised the need for continuous glucose monitoring (CGM) systems, promoting advancements in non-invasive wearable diabetes sensors. This comprehensive review explores the latest developments in this field, focusing on the types, technological advancements, and challenges associated with these devices. The review is structured into distinct sections that examine the current state and future directions of optical, electromagnetic, and transdermal sensors, along with emerging technologies in non-invasive glucose monitoring. The review examines the technological enhancements that have improved sensor accuracy and precision, ergonomic designs for increased comfort, and advancements in data analytics that integrate machine learning for predictive analytics. Comparison of the major challenges such as maintaining sensor accuracy and reliability, ensuring user compliance, safeguarding data privacy, and overcoming cost-related barriers are explored. Furthermore, the paper discusses the promising future directions like the use of innovative materials, the integration of artificial intelligence, and the importance of regulatory and ethical considerations in the development of CGM technologies. This review not only underscores the significant progress made in the field but also highlights the critical need for ongoing research to overcome existing limitations. The implications of these technologies extend beyond individual patient management to broader applications in healthcare and lifestyle monitoring, promoting crucial shift towards more personalised and accessible diabetes management solutions.
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