Abstract
Type 2 diabetes is predicted to become the 7th leading cause of death in the world by the year 2030 [1]. Diabetic foot is the most common long-term diabetic complication, and it is a major risk factor for plantar ulceration (PU), it is determined by peripheral neuropathy (PN), vascular disease, increased foot pressures, foot trauma, deformity and callus [1]. The aim of this study is to develop a methodology for automatic detection of patients at risk for PU based on 3 dimensional (3D) multisegment foot biomechanics through cluster analysis.
Highlights
Type 2 diabetes is predicted to become the 7th leading cause of death in the world by the year 2030 [1]
The aim of this study is to develop a methodology for automatic detection of patients at risk for plantar ulceration (PU) based on 3 dimensional (3D) multisegment foot biomechanics through cluster analysis
Simultaneous kinematic, kinetic and plantar pressure (PP) data were acquired during gait with a BTS motion capture system (6 cameras, 60-120 Hz) synchronized with 2 Bertec force plate (FP4060-10) and 2 Winpod pressure plate as in [2]
Summary
Type 2 diabetes is predicted to become the 7th leading cause of death in the world by the year 2030 [1]. Diabetic foot is the most common long-term diabetic complication, and it is a major risk factor for plantar ulceration (PU), it is determined by peripheral neuropathy (PN), vascular disease, increased foot pressures, foot trauma, deformity and callus [1].
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