Detection of Diabetes Using 1D Convolutional Neural Network from Short Time PPG Signal
Diabetes is a prevalent and chronic condition requiring effective surveillance and
categorization. In recent years, the analysis of physiological signals, such as …
categorization. In recent years, the analysis of physiological signals, such as …
Type 2 diabetes detection with light CNN from single raw PPG wave
Photoplethysmography (PPG) is a non-invasive and cost-efficient optical technique used to
assess blood volume variations inside the micro-circulation. PPG technology is widely used …
assess blood volume variations inside the micro-circulation. PPG technology is widely used …
Deep Learning based non-invasive diabetes predictor using Photoplethysmography signals
VB Srinivasan, F Foroozan - 2021 29th European Signal …, 2021 - ieeexplore.ieee.org
In 2016, World Health Organization (WHO) estimated that diabetes is the seventh leading
cause of death causing 1.6 million casualties globally. In this paper, we propose a non …
cause of death causing 1.6 million casualties globally. In this paper, we propose a non …
Machine learning-based diabetes detection using photoplethysmography signal features
FAC Oliveira, FM Dias, MAF Toledo… - arXiv preprint arXiv …, 2023 - arxiv.org
Diabetes is a prevalent chronic condition that compromises the health of millions of people
worldwide. Minimally invasive methods are needed to prevent and control diabetes but most …
worldwide. Minimally invasive methods are needed to prevent and control diabetes but most …
Type 2 diabetes detection with light CNN from single raw PPG wave
Photoplethysmography (PPG) is a non-invasive and cost-efficient optical technique used to
assess blood volume variations in the microcirculation. PPG technology is widely used in a …
assess blood volume variations in the microcirculation. PPG technology is widely used in a …
Type2 diabetes classification from short photoplethysmogram signal using multiple domain features and machine learning techniques
Purpose Type 2 diabetes is a rapidly growing chronic disease that needs early detection. If
untreated in the initial stage, diabetes-related problems such as retinopathy, neuropathy …
untreated in the initial stage, diabetes-related problems such as retinopathy, neuropathy …
PPG-Based Feature Extraction for Type II Diabetes Prediction: A Machine Learning Approach
The timely and precise diagnosis of diabetes holds paramount importance for efficient
management and prevention of associated complications. While conventional diagnostic …
management and prevention of associated complications. While conventional diagnostic …
Deep Neural Network models for classification of significant attributes to predict Pre-Diabetes Mellitus
B Singh, J Yadav, M Singh… - 2023 5th International …, 2023 - ieeexplore.ieee.org
Hyperglycemia is a chronic condition associated with Pre-diabetes mellitus. It could lead to
many health issues. According to recent increases in morbidity, the number of diabetic …
many health issues. According to recent increases in morbidity, the number of diabetic …
A machine learning approach to predict diabetes using short recorded photoplethysmography and physiological characteristics
C Hettiarachchi, C Chitraranjan - … in Medicine: 17th Conference on Artificial …, 2019 - Springer
Diabetes is a global epidemic, which leads to severe complications such as heart disease,
limb amputations and blindness, mainly occurring due to the inability of early detection …
limb amputations and blindness, mainly occurring due to the inability of early detection …
Non-invasive classification of blood glucose level for early detection diabetes based on photoplethysmography signal
Monitoring systems for the early detection of diabetes are essential to avoid potential
expensive medical costs. Currently, only invasive monitoring methods are commercially …
expensive medical costs. Currently, only invasive monitoring methods are commercially …