Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability
Joint Authors
Trontelj, Janez
Tasic, Jurij
Gusev, Marjan
Poposka, Lidija
Spasevski, Gjoko
Kostoska, Magdalena
Koteska, Bojana
Simjanoska, Monika
Ackovska, Nevena
Stojmenski, Aleksandar
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-06
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Diabetes is one of today’s greatest global problems, and it is only becoming bigger.
Constant measuring of blood glucose level is a prerequisite for monitoring glucose blood level and establishing diabetes treatment procedures.
The usual way of glucose level measuring is by an invasive procedure that requires finger pricking with the lancet and might become painful and obeying, especially if this becomes a daily routine.
In this study, we analyze noninvasive glucose measurement approaches and present several classification dimensions according to different criteria: size, invasiveness, analyzed media, sensing properties, applied method, activation type, response delay, measurement duration, and access to results.
We set the focus on using machine learning and neural network methods and correlation with heart rate variability and electrocardiogram, as a new research and development trend.
American Psychological Association (APA)
Gusev, Marjan& Poposka, Lidija& Spasevski, Gjoko& Kostoska, Magdalena& Koteska, Bojana& Simjanoska, Monika…[et al.]. 2020. Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability. Journal of Sensors،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1190730
Modern Language Association (MLA)
Gusev, Marjan…[et al.]. Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability. Journal of Sensors No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1190730
American Medical Association (AMA)
Gusev, Marjan& Poposka, Lidija& Spasevski, Gjoko& Kostoska, Magdalena& Koteska, Bojana& Simjanoska, Monika…[et al.]. Noninvasive Glucose Measurement Using Machine Learning and Neural Network Methods and Correlation with Heart Rate Variability. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1190730
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190730