Diabetic foot peripheral vascular occlusive disease estimation using fractional-order chaos synchronization detector

This paper proposes a novel method for peripheral vascular occlusive disease (PVOD) estimation in diabetic foot using a fractional-order chaotic system (FOCS). Photo-plethysmography (PPG) is a non-invasive technique for detecting blood volume changes in peripheral arteries. Bilateral PPG signals gradually become asymmetry on the right-site or left-site transit time and pulse shape with PVOD severity and have high correlation. We utilized a FOCS detector to estimate the grades of PVOD by analyzing dynamic errors based on various butterfly patterns, including normal condition (Nor), lower-grade (LG) disease and higher-grade (HG) disease patterns. A color relation analysis (CRA) based classifier is proposed to recognize the various patterns. For 21 subjects, the proposed method showed higher accuracy in estimation of PVOD.