Clinically Validated Classification of Chronic WoundsMethod with Memristor-Based Cellular Neural Network

Abstract Chronic wounds are a syndrome that affects around 4% of the world population due to several pathologies. The COV-19pandemic has enforced the need of developing new techniques and technologies that can help clinicians to monitor the affectedpatients easily and reliably. In this study a new device, the Wound Viewer (WV), that works through a memristor-basedDiscrete-Time Cellular Neural Network (DT-CNN) has been developed and tested through a clinical trial of 150 patients. TheWV has been developed to serve as the state-of-art tool, capable to return the actual clinical information that is most neededby the caregivers. This work aims to describe in depth the technology and the computational techniques that have beenimplemented, and to demonstrate reliability in automatically identifying, classifying through internationally accepted clinicalscales and measuring such wounds, that peaked to over a 90% of accuracy.