Classification of Diabetes Using Photoplethysmogram (PPG) Waveform Analysis: Logistic Regression Modeling
Joint Authors
Qawqzeh, Yousef K.
Bajahzar, Abdullah S.
Jemmali, Mahdi
Otoom, Mohammad Mahmood
Thaljaoui, Adel
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-11
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
In this research, the photoplethysmogram (PPG) waveform analysis is utilized to develop a logistic regression-based predictive model for the classification of diabetes.
The classifier has three predictors age, b/a, and SP indices in which they achieved an overall accuracy of 92.3% in the prediction of diabetes.
In this study, a total of 587 subjects were enrolled.
A total of 459 subjects were used for model training and development, while the rest of the 128 subjects were used for model testing and validation.
The classifier was able to diagnose 63 patients correctly as diabetes while 27 subjects were wrongly classified as nondiabetes with an accuracy of 70%.
Again, the model classified 479 subjects as nondiabetes correctly while it incorrectly classified 18 subjects as diabetes with an accuracy of 96.4%.
Finally, the proposed model revealed an overall predictive accuracy of 92.3% which makes it a reliable surrogate measure for diabetes classification and prediction in clinical settings.
American Psychological Association (APA)
Qawqzeh, Yousef K.& Bajahzar, Abdullah S.& Jemmali, Mahdi& Otoom, Mohammad Mahmood& Thaljaoui, Adel. 2020. Classification of Diabetes Using Photoplethysmogram (PPG) Waveform Analysis: Logistic Regression Modeling. BioMed Research International،Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1133412
Modern Language Association (MLA)
Qawqzeh, Yousef K.…[et al.]. Classification of Diabetes Using Photoplethysmogram (PPG) Waveform Analysis: Logistic Regression Modeling. BioMed Research International No. 2020 (2020), pp.1-6.
https://search.emarefa.net/detail/BIM-1133412
American Medical Association (AMA)
Qawqzeh, Yousef K.& Bajahzar, Abdullah S.& Jemmali, Mahdi& Otoom, Mohammad Mahmood& Thaljaoui, Adel. Classification of Diabetes Using Photoplethysmogram (PPG) Waveform Analysis: Logistic Regression Modeling. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1133412
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133412