Back to Search Start Over

Advanced subsystems based ECG signal classification and processing using deep neural networks and wavelets: An evolution of digital health records.

Authors :
Priyadarsini, M. Jasmine Pemeena
Preetha, R.
Sai, Telaprolu Dinesh Ram
Chowdary, Kasaragadda Tarun Sai
Rahul, Ogirala Uday Venkat
Jabeena, A.
Rajini, G. K.
Source :
AIP Conference Proceedings. 3/27/2024, Vol. 2966 Issue 1, p1-17. 17p.
Publication Year :
2024

Abstract

The electrocardiogram (ECG) shows the plot of the bio-potential produced by the movement of the heart and is utilized by doctors to foresee and treat different cardiovascular illnesses. The arrangement of electrocardiogram (ECG) signals assumes a significant function in the conclusions of heart illnesses. An exact ECG grouping is a difficult issue. Early and precise discovery of arrhythmia, Congestive Cardiovascular breakdown types is significant in distinguishing heart infections and picking suitab le treatment for a patient. Various classifiers are accessible for ECG orders. Among all classifiers, Convolution Neural Organizations (CNNs) like ALEXNET have become exceptionally famous and most broadly utilized for ECG grouping. This paper examined the issues engaged with ECG order and presents a definite studyof pre-handling strategies, ECG information bases, highlight extraction methods, CNN-based classifiers, and execution measures to address the referenced issues using the IoT-based mechanisms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2966
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
176251495
Full Text :
https://doi.org/10.1063/5.0189843