28 天前 - … In quest of non-invasive solution to measure blood glucose… , Machine learning
algorithms for diabetes prediction and … using non-invasive digital photoplethysmography, Blood …

37 天前 - … of machine learning-based approaches in predicting blood sugar levels from PPG
signals. … for improved diabetes management through accurate, non-invasive, and data-driven …

55 天前 - … A photoplethysmography (PPG) signal integrated with machine learning is currently
… (TinyML) and tested in real-time environment for continuous non-invasive predictions of …

80 天前 - … Hariharan, "Non-invasive prediction of hemoglobin level using machine learning
techniques with the PPG signal's characteristics features," Applied Soft Computing, vol. 37, pp. …

122 天前 - … deep learning algorithms on a Raspberry Pi, the system is equipped with data
collection, analysis, prediction, … Photoplethysmography (PPG) is a non-invasive optical technique …

145 天前 - … a non-invasive approach to estimate blood glucose levels using photoplethysmography
(… It focuses on fasting blood glucose prediction using wrist PPG signals and explores …

156 天前 - … non-invasive methodology for diabetes detection through the utilization of
Photoplethysmogram (PPG) signals… each feature in diabetes prediction is assessed through …

293 天前 - … They reported 5.84 mg/dl as the root mean squared error of prediction using double
… on machine learning based blood glucose estimation from photoplethysmography signal. …