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Updated: May 10, 2025

Fabrication and Characterization of a Conformal Skin-like Electronic System for Quantitative, Cutaneous Wound Management
Published on: September 2, 2015
A microfluidic wearable device for wound exudate management and analysis in human chronic wounds
Canran Wang1, Kexin Fan1, Ehsan Shirzaei Sani1,2
1Andrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA.
Abstract:
Chronic wounds are a major global health challenge associated with substantial economic burden and a negative impact on patient quality of life. Real-time analysis of biomarkers like reactive oxygen and nitrogen species could guide treatment, but existing systems lack the capacity required for continuous monitoring. Wound exudate is secreted slowly and has a complex composition, making efficient fluid collection and real-time analysis challenging. To address these issues, we introduce iCares, a wearable device for wound exudate management and continuous in situ analysis of wound biomarkers. iCares contains a flexible nanoengineered sensor array that measures reactive species such as NO, H2O2, and O2, along with pH and temperature, providing multiparameter data to inform wound status. The device features pump-free triad microfluidic modules with a superhydrophobic-superhydrophilic Janus membrane, bioinspired wedge channels, and three-dimensional graded micropillars for efficient unidirectional exudate collection, transport, and refreshing. The sensors demonstrated a consistent response and analyte selectivity in vitro and in wound exudate. iCares was designed for rapid scalable manufacturing through advanced printing and laser patterning. Wireless connectivity supported long-term continuous monitoring in wounds. The iCares system real-time monitoring was tested in a murine model of diabetic skin wound during infection and antimicrobial treatment. Clinical wound evaluation was conducted in 20 patients with chronic wounds and in two patients before and after surgery. A machine learning analysis of the multiplexed data successfully classified wounds and healing times, indicating that wound exudate analysis by iCares could offer insight into chronic wound status to aid in treatment decisions.

