Noninvasive Technique for Diabetic Prediction Using ECG and PPG Signal Parameters

  • N. Kasthuri, V. Sathya Narayanan, A. M. Hari Shri Ram, S. Jaishree, R. Krishna Prasath, M. Mohamed Arish


In India almost 12% of the population are affected by diabetics and it is the 8th leading cause of death. People are affected by Diabetics across the world and it is more common in the developed countries. According to the report of WHO the prevalence of diabetics will get doubled by 2025. The diabetics can lead to tissue damage and organ failure and this presents a serious public health challenge to a country facing a future of high population growth. The persons affected by diabetics needs to diagnose the diabetic level periodically to maintain the normal level. Normally blood test to be done to find the blood glucose level. Diabetes is diagnosed with fasting sugar blood tests also known as glycated haemoglobin test and after fasting test to be done again. As people afraid of the injection for giving the blood samples, they are refused to take the periodical test. In this paper, noninvasive method of identification is proposed to find whether the person is diabetic or not by deriving suitable parameters from the PPG and ECG signal acquired. The ECG and PPG signals are taken from human subject using the biomedical kit. With the help of that signal the analysis process is carried out. The signals are filtered to avoid power -line interference and muscle artifacts. The R-wave peak is detected and the distance between two consecutive R-waves are found. With the help of RR interval the heart rate and the parameters are found. The aim of this paper is to analyze the ECG and PPG signal from human subject and predict the heart condition in real time that reveals the health condition of a particular human being in various condition such as presence of Diabetics, pressure and being normal. This also helps to monitor the performance of the heart through heart rate variability, so that a sportsman health can be monitored during intense activities and hence identify any abnormalities.

How to Cite
R. Krishna Prasath, M. Mohamed Arish, N. K. V. S. N. A. M. H. S. R. S. J. (2020). Noninvasive Technique for Diabetic Prediction Using ECG and PPG Signal Parameters. International Journal of Advanced Science and Technology, 29(3), 6504 - 6512. Retrieved from