AI-enabled wearable microfluidics for next-generation infection monitoring and therapeutics

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Authors: Yan Zhou, Xiaoyu Zhu, Kai Qu, Feng Xu
Cited by: 8
References: 174

Abstract

Wearable biosensors have revolutionized healthcare by enabling continuous, minimally invasive monitoring of health parameters. While traditional wearables primarily measure physiological signals, recent advancements now allow biochemical sensing of microbial biomarkers across diverse human biofluids, including sweat, saliva, wound exudate, interstitial fluid, tears, breath, and urine. These biomarkers, including microbial nucleic acids, metabolites, and host immune mediators, provide valuable information for diagnosing and managing infections. Wearable microfluidic devices are designed to sample these biofluids directly from the body and allow for rapid identification of microbial signatures and associated host responses. Moreover, some wearables' use of living microorganisms as functional components has opened new opportunities for biosensing and therapeutic delivery. The integration of artificial intelligence improves the interpretation of complex and dynamic data streams, and facilitates precise and adaptive decision-making. Additionally, by addressing biomechanical interactions between microorganisms, host tissues, and wearable interfaces, mechanomedicine principles provide insights into these systems. In the near future, these interdisciplinary innovations have the potential to transform infection control, personalized healthcare, and global health surveillance.

Fields of Study & Subjects

Biosensors and Analytical Detection Advanced Sensor and Energy Harvesting Materials Microfluidic and Bio-sensing Technologies

Publication details

Journal / source
Lab on a Chip
Publisher
Royal Society of Chemistry (RSC)
Volume
26
Issue
5
Pages
1489–1509
Publication date
1 January 2026
Language
EN