Automated detection of diabetes using higher order spectral features extracted from heart rate signals - Swapna, Goutham (2013)
Diabetes Mellitus, often referred to as diabetes, is a chronic disease that affects a vast majority of world population. The percentage of people affected is increasing every year. Diabetes is very difficult to cure. It can only be kept under control. In this scenario, diagnosis of diabetes is of great importance. In this work, we used Heart Rate Variability (HRV) signals obtained from ECG signals for the purpose of diagnosis of diabetes. We employed signal processing methods to extract features from the HRV signal. Since HRV signals are of nonlinear nature, we made use of Higher Order Spectrum (HOS) based features for analysis. In this paper, we have extracted the HOS features from HRV signals corresponding to normal and diabetic subjects.