In this paper, application of Artificial Neural Network (ANN) for electrocardiogram (ECG) signal noise removal has been investigated. First, 100 number of ECG signals are selected from Physikalisch-Technische Bundesanstalt (PTB) database and Kalman filter is applied to remove their low pass noise. Then a suitable dataset based on denoised ECG signal is configured and used to a Multilayer Perceptron (MLP) neural network to be trained. Finally, results and experiences are discussed and the effect of changing different parameters for MLP training is shown.
Various studies, especially in recent years, have shown that quercetin has beneficial therapeutic effects in various human diseases, including diabetes. Quercetin has significant anti-diabetic effects and may be helpful in lowering blood sugar and increasing insulin sensitivity. Quercetin appears to affect many factors and signaling pathways involved in insulin resistance and the pathogenesis of type 2 of diabetes. TNFα, NFKB, AMPK, AKT, and NRF2 are among the factors that are affected by quercetin. In addition, quercetin can be effective in preventing and ameliorating the diabetic complications, including diabetic nephropathy, cardiovascular complications, neuropathy, delayed wound healing, and retinopathy, and affects the key mechanisms involved in the pathogenesis of these complications. These positive effects of quercetin may be related to its anti-inflammatory and anti-oxidant properties. In this article, after a brief review of the pathogenesis of insulin resistance and type 2 diabetes, we will review the latest findings on the anti-diabetic effects of quercetin with a molecular perspective. Then we will review the effects of quercetin on the key mechanisms of pathogenesis of diabetes complications including nephropathy, cardiovascular complications, neuropathy, delayed wound healing, and retinopathy. Finally, clinical trials investigating the effect of quercetin on diabetes and diabetes complications will be reviewed.