IoMT-Based Wearable Sweat Sensors: A Systematic Review of Non-Invasive Biomarker Monitoring for the Management of Metabolic Diseases
Abstract
Metabolic diseases such as type 2 diabetes mellitus, obesity, and metabolic syndrome continue to represent a growing global health burden. Conventional invasive monitoring methods often cause discomfort, repeated skin injury, and increased risk of infection, thereby encouraging the development of non-invasive monitoring technologies based on the Internet of Medical Things (IoMT). This systematic literature review aimed to synthesize recent advances in IoMT-based wearable sweat sensors as non-invasive biomarker monitoring platforms for metabolic disease management. A systematic literature search was conducted in PubMed and Google Scholar for articles published between 2021 and 2026 using keywords related to wearable sensors, sweat biomarkers, IoMT, and metabolic diseases. Following eligibility screening, 36 studies were included and analyzed. The findings revealed rapid advancements in wearable sweet-sensing technologies, particularly electrochemical, colorimetric, and microfluidic platforms integrated with IoMT architectures. Major biomarkers monitored through glucose, lactate, cortisol, and inflammatory cytokines such as IL-6 and TNF-α. Several studies demonstrated strong correlations between sweat biomarkers and conventional clinical measurements, while IoMT architectures integrated with Bluetooth Low Energy (BLE) and machine learning enabled accurate real-time monitoring. Overall, IoMT-based wearable sweat sensors demonstrate considerable potential as non-invasive tools…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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