ReviewNano-micro letters2025
Noninvasive On-Skin Biosensors for Monitoring Diabetes Mellitus.
Review in Nano-micro letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Wearable Electronics for Precision Diagnosis Through Advanced Manufacturing and Integration.Nano-micro letters · 2026Review
- High-Sensitivity Non-Invasive Microwave Glucose Sensor with ZnO/CNT Composite Optimized by Deep Learning for Wearable Medical Devices.ACS omega · 2026Article
- Innovative strategies for diabetic peripheral neuropathy: From clinical management to emerging bioengineering solutions.Bioactive materials · 2026Review
- Upconverting Nanoparticles for Bimodal Luminescence and Magnetic Resonance Imaging of Langerhans Islets.Small science · 2026Article
- Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.Journal of materials science. Materials in medicine · 2026Review
- Wearable Multifunctional Sensors for Human Activity Recognition.Sensors (Basel, Switzerland) · 2026Review
- Glycemic Variability and Gut Microbiota Metabolic Patterns: A Novel Perspective on Diabetic Complications.Food science & nutrition · 2025Review
- Type 5 diabetes mellitus: redefining pancreatogenic diabetes through molecular, imaging, and AI-driven evidence.Frontiers in endocrinology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.