• NETRA PATIL
• DR. NAVEENKUMAR JAYAKUMAR

Diabetes Mellitus (DM) is a metabolic diseases group where the person will have high blood sugar due to the pancreas unable to produce sufficient insulin or the cell’s which are not responding to the insulin produced. Diabetes is a chronic disease and a major public health challenge worldwide. The main drawback is that there is lack of awareness of the people on eating habits. In our country, diabetes patient counts have increased steadily due to this reason. Diabetes is a metabolic disease affecting a multitude of people worldwide. Its incidence rates are increasing alarmingly every year. If untreated, diabetes-related complications in many vital organs of the body may turn fatal. Early detection of diabetes is very important for timely treatment which can stop the disease progressing to such complications. RR-interval signals known as heart rate variability (HRV) signals (derived from electrocardiogram (ECG) signals) can be effectively used for the non-invasive detection of diabetes. This research paper presents a methodology for classification of diabetic and normal HRV signals using deep learning mechanism. We employ long short-term memory (LSTM), convolutional neural network (CNN) and its combinations for extracting complex temporal dynamic features of the input HRV data. These features are passed into support vector machine (SVM) for classification. We have obtained the performance improvement of 0.03% and 0.06% in CNN and CNN-LSTM architecture respectively compared to our earlier work without using SVM. The classification system proposed can help the clinicians to diagnose diabetes using ECG signals with a very high accuracy of 95.7%.

Deep learning, Diabetes, Heart rate variability, ECG, CNN, LSTM.

"A MODEL FOR PREDICTING TYPE-II DIABETES USING MACHINE LEARNING APPROACH ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.288-295, March-2021, Available :http://www.jetir.org/papers/JETIR1908657.pdf

"A MODEL FOR PREDICTING TYPE-II DIABETES USING MACHINE LEARNING APPROACH ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp288-295, March-2021, Available at : http://www.jetir.org/papers/JETIR1908657.pdf