Classification of Doppler Ultrasound Blood Flow Signals of Lower Extremity Arteries for the Early Detection of Diabetic Foot

Peripheral arterial disease is one of the key indicators diabetic foot, which can be easily identified by ultrasound diagnostic techniques. The work aims to detect foot in early stages classifying blood flow signals lower extremity arteries being captured doppler methods. Samples are collected from patients with and without having probable symptoms diseases. Doppler examination has been conducted on posterior tibial artery for 354 subjects a transducer 8 MHz frequency. auscultation, method listening sounds internal organs, employed as medical tool identifying pathological conditions. Each human body unique profile flow. This fixed may changed presence particular disease. received signal spectrum Doppler-shifted respect existence velocity across vessel lumen. Changes shape this an indicator severity Various features extracted using various statistical processing functions. feature analysis was accomplished machine learning algorithms. Naïve Bayes, Tree SVM algorithms MATLAB Toolboxes. Comparing performance these algorithms, found superior than others. So, proposed classification methodology factor stage detection foot. As correlated many other parameters effects pressure extremities, integrated prediction model incorporating technique.