Project

Non-Invasive Estimation of Cholesterol through Photoplethysmography leveraging IoMT and AI 

Cholesterol, a crucial substance in our bodies, and its excessive amounts leads to cardiovascular diseases and strokes. These have contributed highly to the rising health issues and fatality rate. Keeping cholesterol in Current methods for monitoring blood cholesterol are invasive and complex. To address this, our project proposes a non-invasive approach using photoplethysmography (PPG). PPG signals, captured optically with a sensor device, will be analyzed for feature extraction. These features will then undergo correlation analysis with cholesterol levels using deep learning algorithms. 

The proposed solutions have the potential to revolutionize healthcare by enabling remote monitoring and timely intervention for individuals at risk of CVDs. By providing accessible and non-invasive monitoring solutions, this project aims to improve the quality of healthcare delivery, particularly in resource-constrained settings. 

Publication Details

•  A. C. B, D. Padmavilochanan, R. K. Pathinarupothi, K. A. U. Menon, S. Chandra and G. K. P. M, “Minimal Features based Non Invasive Cholesterol Computation using Machine Learning,” 2023 3rd International Conference on Intelligent Technologies (CONIT), Hubli, India, 2023, pp. 1-8, doi: 10.1109/CONIT59222.2023.10205812. 

Patent Details 

• Ramesh, Maneesha Vinodini, Rahul Krishnan Pathinarupothi, Ekanath Srihari Rangan, P. Durga, and P. Venkat Rangan. “Systems, methods, and devices for remote health monitoring and management using internet of things sensors.” U.S. Patent 10,433,726, issued October 8, 2019. 
• Ramesh, Maneesha Vinodini, Rahul Krishnan Pathinarupothi, and Ekanath Srihari Rangan. “Systems, methods, and devices for remote health monitoring and management.” U.S. Patent 10,542,889, issued January 28, 2020.