Name
Title | ||
|---|---|---|
Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers. |
Abstract | ||
|---|---|---|
•An ensemble of SVMs is proposed for ECG arrhythmia classification.•Each SVM model is trained on a different set of features.•Ensemble of SVMs improves the results of a single SVM.•The public MIT-BIH arrhythmia database is employed for all experiments. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.bspc.2018.08.007 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
Electrocardiogram (ECG),Heartbeat classification,Support vector machine (SVM),Combining classifiers,Ensemble of classifiers | Heartbeat,Pattern recognition,Higher-order statistics,Local binary patterns,Support vector machine,Concatenation,Artificial intelligence,Majority rule,Mathematics,Wavelet | Journal |
Volume | ISSN | Citations |
47 | 1746-8094 | 9 |
PageRank | References | Authors |
0.57 | 23 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| V. Mondéjar-Guerra | 1 | 9 | 0.57 |
| Jorge Novo | 2 | 25 | 6.18 |
| Jose Rouco | 3 | 55 | 10.41 |
| Manuel G. Penedo | 4 | 185 | 35.91 |
| M Ortega | 5 | 235 | 37.13 |