| Abstract |
With advanced computing and communication technologies, there have been many attempts to provide optimum healthcare services in the last decades. The digital twin is one of the emerging technologies that promise personalized and predictive healthcare. The digital twin concept has been broadly accepted in many fields, such as manufacturing, construction, smart building, smart grids, smart cities, and more. However, its application in healthcare is still in its infancy. This chapter will thoroughly examine the potential of digital twins in chronic wound management. At first, an organic digital twin of a chronic wound will be built by considering patients' information, such as gender, age, and images of his/her wound. After the organic twin of the same chronic wound is created as a biological model, both wounds in a digital environment, as well as the patient's wound, in reality, will start healing. After several weeks or months, when the patient returns to the hospital, the digital twin will be compared to the current status of the real wound. All of the collected information affects the digital clone of the actual chronic wound, enabling monitoring and modifying wound healing status proactively with state-of-the-art techniques, such as artificial intelligence. In addition, the time for the digital twin can be sped up so that wound could be aged faster to oversee healing progress, e.g., in three minutes, we are able to simulate the healing process for three weeks. This chapter analyzes the current chronic wound management techniques and puts forward the digital twin concept in chronic wound management. The digital twin in chronic wound management will shed light on providing optimal treatment pathways and better interpretation of the treatment. This chapter explores digital twin applications in healthcare and reviews chronic wounds and enabling technologies to further understand the application of the digital twin concept on chronic wounds. Then the chronic wound management system using the digital twin concept is discussed. It also describes the wound management framework architecture using wound images. © The Author(s). |
