| Full text | |
| Author(s): |
Amorim, Paulo
[1]
;
Moraes, Thiago
[1]
;
Fazanaro, Dalton
[2]
;
Silva, Jorge
[1]
;
Pedrini, Helio
[2]
Total Authors: 5
|
| Affiliation: | [1] Ctr Informat Technol Renato Archer, Tridimens Technol Div, BR-13069901 Campinas, SP - Brazil
[2] Univ Estadual Campinas, Inst Comp, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE; v. 161, p. 125-132, JUL 2018. |
| Web of Science Citations: | 5 |
| Abstract | |
Background and Objective: Cardiac arrhythmia is an abnormal variation in the heart electrical activity that affects millions of people worldwide. Electrocardiogram (ECG) signals have been widely used to assess and diagnose cardiac abnormalities. Methods: A novel methodology based on shearlet and contourlet transforms for automatically classify an input ECG signal into different heart beat types is proposed and evaluated in this work. Classifiers are trained through a set of features extracted from these time-frequency coefficients. Results: Tests are conducted on MIT-BIH data set to demonstrate the effectiveness of the proposed classification method. The shearlet and contourlet transforms achieved high classification accuracy rates. Conclusions: The developed system can help cardiologists obtain structural and functional information of the heart by means of ECG patterns, improving their diagnostic tasks. (C) 2018 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Research Projects - Thematic Grants |