One in three people living with diabetes are affected by diabetic foot ulcers (DFUs) which, if left unmonitored and untreated, reduce quality of life, and may lead to foot amputation. Regular foot screening is suggested by relevant national guidelines. Yet, compliance with screening is poor, mostly due to the inconvenience of the screening process itself. In this work, we describe a preliminary version of a simple low-cost device intended for self-monitoring of foot circulation, to identify the areas of poor perfusion expected to be at the root of the formation of DFUs. This device is based on multispectral imaging of the feet in the visible and near-infrared ranges. The device is tested on the hands and feet of a single subject, where impairment of circulation has been simulated through a brief ligature of a finger/two toes. Multispectral images are captured, and a simple machine-learning-based classifier correctly identifies areas of low perfusion on the hand and shows promising data on toes. Albeit the device and the classifier are still susceptible of significant improvement, this is indicative of the fact that the multispectral images contain relevant information on tissue perfusion.
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