Publication

Abstract : Peripheral arterial disease (PAD) is defined as the deficiency of oxygen rich blood to organs especially to lower extremities. PAD is caused due to shrinking of arteries and it is very difficult to identify the disease in its beginning stage. PAD is often diagnosed when it develops complications and in worst case it may even lead to leg amputation. This indicates that early detection of PAD is essential. But the existing method to detect PAD is time consuming, inefficient and requires assistance of expertise. Blood oxygen saturation (SPO 2 ) level can serve as early warning of PAD. A simulation model to detect PAD based on SPO 2 levels is presented in this paper. Non-invasive measurement of SPO 2 can be done using photoplethysmography (PPG). Pre-processing of the PPG signals are done. Gaussian filter and Hamming filter are implemented. Signal to noise ratio (SNR) of the filtered and unfiltered signals are done. An algorithm to compute SPO 2 values from PPG signals and to detect PAD is presented. In addition a novel algorithm is developed to compute heart rate from PPG signal. Error analysis on the SPO 2 and heart rate values of both Gaussian and hamming filtered signals is also done in this paper.