Name
Abstract | ||
|---|---|---|
The proposed method obtained good results in both fQRS detection and quantification, and is a novel way of assessing the certainty of QRS fragmentation in the ECG signal. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JBHI.2018.2878492 | IEEE journal of biomedical and health informatics |
Keywords | Field | DocType |
Electrocardiography,Feature extraction,Lead,Machine learning,Support vector machines,Databases,Training | Pattern recognition,Naive Bayes classifier,Computer science,Variational mode decomposition,Support vector machine,Feature extraction,QRS complex,Artificial intelligence,Electrocardiography,Signal averaging,Myocardial scarring | Journal |
Volume | Issue | ISSN |
23 | 5 | 2168-2208 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Griet Goovaerts | 1 | 4 | 3.89 |
| Padhy, S. | 2 | 16 | 3.29 |
| b vandenberk | 3 | 3 | 2.13 |
| Carolina Varon | 4 | 92 | 22.90 |
| Rik Willems | 5 | 7 | 5.17 |
| Sabine Van Huffel | 6 | 1058 | 149.38 |