{'fraction_non_alphanumeric': 0.01685823754789272, 'fraction_numerical': 0.00842911877394636, 'mean_word_length': 5.018433179723503, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Memristor Based Integrated System for the Long-Term Analysis of Chronic Wounds: Design and Clinical Trial

Before the COVID-19 pandemic, it was known that chronic wounds affected roughly 2% of the world population. Due to the increase of bedridden patients parting from 2020, it is estimated that the number of affected people in the world has risen to around 4%. Moreover, there is a constant need coming directly from the medical community, for new devices that can help the tele-monitoring of chronic syndromes such as cutaneous ulcers. In the last years our research group has committed itself in the development of the WoundViewer, an integrated telemedical device able to automatically analyse chronic wounds though a Memristor Cellular Automata (MCA) designed and trained for this specific scope. This work will present both the design of the MCA and of the device, and the data obtained form the clinical trial preformed with the device on a cohort of 150 patients suffering from three different kinds of chronic wounds at different states. The presented data proves that the use systems that exploit memristor-based computing techniques can provide useful and much needed advantages in different actual critical fields such as patient care, helping caregivers to maintain a high standard of cure.