可穿戴计算机
计算机科学
可穿戴技术
医学
分析
个性化医疗
生物标志物
风险分析(工程)
数据科学
生物信息学
嵌入式系统
生物
生物化学
作者
Ali Sedighi,Tianyu Kou,Hui Huang,Yi Li
出处
期刊:Nano-micro Letters
[Springer Science+Business Media]
日期:2025-07-31
卷期号:18 (1): 16-16
被引量:3
标识
DOI:10.1007/s40820-025-01843-9
摘要
Diabetes mellitus represents a major global health issue, driving the need for noninvasive alternatives to traditional blood glucose monitoring methods. Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers, providing innovative solutions for diabetes diagnosis and monitoring. This review comprehensively discusses the current developments in noninvasive wearable biosensors, emphasizing simultaneous detection of biochemical biomarkers (such as glucose, cortisol, lactate, branched-chain amino acids, and cytokines) and physiological signals (including heart rate, blood pressure, and sweat rate) for accurate, personalized diabetes management. We explore innovations in multimodal sensor design, materials science, biorecognition elements, and integration techniques, highlighting the importance of advanced data analytics, artificial intelligence-driven predictive algorithms, and closed-loop therapeutic systems. Additionally, the review addresses ongoing challenges in biomarker validation, sensor stability, user compliance, data privacy, and regulatory considerations. A holistic, multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.
科研通智能强力驱动
Strongly Powered by AbleSci AI