Electrocardiogram signal pattern recognition using PCA and ICA on different databases for improved health management
by Varun Gupta; Natwar Singh Rathore; Amit Kumar Arora; Sharad Gupta; Abhas Kanungo; Salim; Neeraj Kumar Gupta
International Journal of Applied Pattern Recognition (IJAPR), Vol. 7, No. 1, 2022

Abstract: Due to non-invasive and easy to acquire procedure, electrocardiogram (ECG) is broadly adopted for extracting the correct heart health status of the subject (patient). In this paper, a method of analysing ECG signals (based on R-peak detection) recorded during different postures (i.e., sitting, standing and supine) has been presented. The results of this analysis are also compared with standard physioNet database (MIT-BIH arrhythmia database) for validation. Real time ECG signals in all three postures were acquired for 500 subjects, out of which signals of 17 subjects are used for analysis. For filtering these subjects' recordings, existing techniques need a higher order of analogue and digital filters. It increases the complexity of the system, which motivated us to use the combination of principal component analysis (PCA) and independent component analysis (ICA). This combination fulfils the need of higher order filters (HOFs). PCA is used for dimension reduction, whereas ICA is used for noise removal.

Online publication date: Thu, 14-Apr-2022

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 Applied Pattern Recognition (IJAPR):
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