Towards non-invasive blood glucose measurement using machine learning: An all-purpose PPG system design-Reference-Cited by-同舟云学术

Towards non-invasive blood glucose measurement using machine learning: An all-purpose PPG system design

Published:2021-07 Issue: Volume:68 Page:102706
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Sen Gupta Shantanu,Kwon Tae-Ho,Hossain Shifat^ORCID,Kim Ki-Doo^ORCID

Funder

Ministry of Science, ICT and Future Planning

National Research Foundation of Korea

Kementerian Pendidikan Malaysia

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

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4. Motion-tolerant magnetic earring sensor and wireless earpiece for wearable photoplethysmography;Poh;IEEE Trans. Inf. Technol. Biomed.,2010

5. Development and evaluation of a wristwatch-type photoplethysmography array sensor module;Lee;IEEE Sens. J.,2013

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4. Internet of Things enabled open source assisted real-time blood glucose monitoring framework;Scientific Reports;2024-03-14

5. Non-Invasive Blood Glucose Estimation Based on Machine Learning Algorithms Using PPG Signals;2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2024-02-19