Artificial Intelligence-Assisted Conductive Hydrogel Dressings for Refractory Wounds Monitoring

Abstract Refractory wounds cause significant harm to the health of patients and the most common treatments in clinical practice are surgical debridement and wound dressings. However, certain challenges, including surgical difficulty, lengthy recovery times, and a high recurrence rate persist. Conductive hydrogel dressings with combined monitoring and therapeutic properties have strong advantages in promoting wound healing due to the stimulation of endogenous current on wounds and are the focus of recent advancements. Therefore, this review introduces the mechanism of conductive hydrogel used for wound monitoring and healing, the materials selection of conductive hydrogel dressings used for wound monitoring, focuses on the conductive hydrogel sensor to monitor the output categories of wound status signals, proving invaluable for non-invasive, real-time evaluation of wound condition to encourage wound healing. Notably, the research of artificial intelligence (AI) model based on sensor derived data to predict the wound healing state, AI makes use of this abundant data set to forecast and optimize the trajectory of tissue regeneration and assess the stage of wound healing. Finally, refractory wounds including pressure ulcers, diabetes ulcers and articular wounds, and the corresponding wound monitoring and healing process are discussed in detail. This manuscript supports the growth of clinically linked disciplines and offers motivation to researchers working in the multidisciplinary field of conductive hydrogel dressings.