Microneedle wearables in advanced microsystems: Unlocking next-generation biosensing with AI

Abstract

Wearable electronics have transformed health monitoring, but the non-invasive, real-time extraction of biomarkers from interstitial fluid (ISF) remains a complex challenge. Microneedle (MN) technologies, integrated with bioelectronics and artificial intelligence (AI), provide a promising solution for continuous health monitoring and personalized therapy. This review explores the design of MN platforms and key sampling mediums, highlighting their role in advanced biosensing applications. It delves into conventional and emerging sensing modalities detailing their integration strategies. Additionally, MN-based assays for biomarkers including glucose, lactate, pH, electrolytes, nucleic acids, and proteins are examined, emphasizing their potential in early disease diagnostics. The review highlights key challenges in the clinical translation of MN-based devices and the integration of AI for improved biomarker calibration. Emerging materials and AI-driven MN platforms show promise for advancing personalized, real-time diagnostics and therapies. However, overcoming issues with ISF biomarker variability, data reliability, and scalability is crucial for their broader clinical adoption.