In vivo validation of a smart sensor-enabled dressing for remote wound monitoring

Abstract

Every second, a person with diabetes develops a foot ulcer. At least half of these wounds become infected, which dramatically increases the risk of hospitalization, amputation, and death. Wound environment pH is a possible marker of infection, however, clinical application has yet to be achieved. Herein, we introduce a hydrogel sheet dressing made out of a transparent calcium alginate body, which is embedded by a pH-sensitive color changing dye named α-naphtholphthalein that equilibrates to wound pH and can classify wound infection risk. We evaluated the moisture handling properties, conformability, and ability to function as an effective barrier to external pathogens. A literature meta-analysis was employed to define pH thresholds associated with risk of wound infection and the smart dressing's sensors were formulated to display easily interpretable colors that contrast with the wound bed and are not impacted by varying backgrounds. The sensors facilitate a machine learning enabled smartphone application that objectively classifies the wounds and can be used for remote wound monitoring. The safety profile of the device was extensively evaluated in vitro and in vivo using 2D cell culture and a robust porcine wound healing model. Finally, in vivo performance validation in mice and pigs demonstrated the impact of bioburden on wound pH and the ability of the smart dressing to indicate states of infection. Images of the smart dressing on mouse wounds were used in a survey to showcase how infection risk classification can be used to triage patients and reduce the burden of wound care on the healthcare system.