Smart Bandages for Chronic Wound Sampling, Monitoring, and Management

Author: Wang, Canran

Year: 2026

Degree: Dissertation (Ph.D.)

Advisor: Gao, Wei

Committee Members: Demirer, Gozde S.; Gao, Wei; Newman, Dianne K.; Mazmanian, Sarkis K.; Zhang, Anqi

Option: Medical and Electrical Engineering

DOI: 10.7907/cq9y-x940

Abstract

Chronic wounds are a major global health issue, incurring staggering economic costs and severely impacting patient well-being. Effective exudate management is crucial, yet current methods fail to balance moisture levels. Real-time analysis of biomarkers like reactive oxygen and nitrogen species could guide treatment, but existing systems lack the capacity required for continuous monitoring. Although wearable electronics have the potential to advance wound care, efficient management and analysis of wound exudate in real time remains challenging owing to its low secretion rate and complex composition. To address these issues, we introduce iCares, a wearable device for wound exudate management and continuous in situ analysis of crucial wound biomarkers. iCares contains a flexible nanoengineered sensor array that measures key reactive species such as NO, H₂O₂, and O₂, along with pH and temperature, providing multiparameter data to inform wound status. The device features a pump-free triad microfluidic modules with a superhydrophobic–superhydrophilic Janus membrane, bioinspired wedge channels, and 3D graded micropillars for efficient unidirectional exudate collection, transport, and refreshing. The sensors demonstrate consistent response and analyte selectivity, validated in wound exudate. Rapidly manufacturable through advanced printing and laser-patterning techniques, iCares seamlessly integrates Bluetooth connectivity and enables scalable, wireless, long-term continuous reactive species monitoring without impeding daily activities. The iCares system was validated through in vivo testing in murine models of infection and fasting, where real-time monitoring was performed. In addition, clinical evaluation was conducted in 20 patients with chronic wounds, as well as in patients monitored before and after surgery, demonstrating the system’s applicability across diverse wound conditions. iCares offers early infection detection and wound classification and outcome prediction using machine learning-enhanced data analysis.

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