الفهرس | Only 14 pages are availabe for public view |
Abstract Foot problems in patients with diabetes mellitus are of major public health concern these days. Due to sensory neuropathy, patients are unable to sense pressure, pain or micro-trauma in or on the foot. An increase in pressure not only hinders blood supply to the pressured surface, but also increases the risk of ulcer development. Unhealed or infected diabetic foot ulcers are a major risk factor for lower-extremity amputation. In this thesis, an analysis system has been implemented to evaluate the characteristics of plantar pres- sure distribution in normal subjects and diabetic patients with and without peripheral neuropathy. A unique feature of the system is to utilize spatial and temporal dynamic plantar pressure measurements. Using machine learn- ing techniques, we classify between the three patient groups which allows early detection and hence the possibility of preventing foot ulcers in diabetic patients |