Artificial Intelligence (AI)-enabled multimodal & cross spectrum photodetectors for management of diabetic foot ulcers

Diabetes mellitus represents a major public health concern worldwide, with an estimated prevalence of approximately 9.1% of the population in Europe imposing a substantial economic burden on healthcare systems. One of the main complications of diabetes is the presence of Diabetic Foot Ulcers (DFUs) arising primarily from neuropathic and vascular impairments. Recent advances in sensing devices and photonics have stimulated the launch of sensors and imaging modules that can early diagnosis and prevent DFUs. In this paper we present the results of a new innovative, reliable, and cost-effective photonic-based system for the monitoring and management of DFUs, designed for large-scale clinical and home use. The system, developed within the framework of the H2020 PHOOTONICS project, integrates passive infrared photodetectors with active illuminators to achieve enhanced diagnostic capability. In PHOOTONICS project, two new photonic technologies for the early diagnosis and the management of diabetic foot have been developed; The professional device, called PRO and the home device called, HOME. The PRO version is dedicated for physicians at their offices or at hospitals. In this article, we present the clinical validation results of the new photonic-based device for diabetic foot ulcer. The results have been validated across four hospitals; ATTIKON University Hospital (Greece), VBMS University Hospital (Romania), CHARITE University Hospital (Germany), LEIDEN University Hospital (Netherlands). The validation includes (i) requirement process of diabetic and non-diabetic patients, patients stratification procedures, existence of comorbidities and an AI-based assessment of the results. For the latter we utilize ResNet deep models.