Identification of type-2 diabetes by electrocardiogram signal using flexible analytical wavelet transform
by Bhanupriya Mishra; Neelamshobha Nirala
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 43, No. 3, 2023

Abstract: Type-2 diabetes mellitus (T2DM) is a lifelong metabolic disease with worldwide prevalence. It can drastically decrease the life expectancy of any subject with a huge economic burden. The present study aimed to create a non-invasive and economical tool for automatic detection of T2DM using electrocardiogram (ECG) signals. The flexible analytic wavelet transform is used to evaluate the ECG by decomposing it into predictable sub-bands. Statistical and time-domain features were extracted from each sub-band. Different feature selection techniques were applied to obtain the most relevant features. The top nine features, selected by using the one-R attribute eval feature selection technique, were fed into the various types of machine learning classifiers. In tested classifiers, the fine k-nearest neighbour and optimisable KNN classifiers have shown the highest average accuracy of 94.94% and 94.61% respectively. The results suggest that the proposed approach provides an efficient non-invasive T2DM detection method in regular applications.

Online publication date: Mon, 30-Oct-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biomedical Engineering and Technology (IJBET):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com