Name
Title | ||
|---|---|---|
Automatic Detection of Atrial Fibrillation and Flutter - A Tachogram-based Algorithm for Mobile Devices |
Abstract | ||
|---|---|---|
Two versions of a new detector for automatic real-time detection of atrial fibrillation and atrial flutter in non-invasive ECG signals are introduced. The methods are based on beat to beat variability, tachogram, analysis and simple signal filtering. The implementation on mobile devices is made possible due to the low demand on computing power of the employed analysis procedures. The proposed algorithms correctly identified 436 of 440 five minute episodes of atrial fibrillation or flutter and also correctly identified up to 302 of 342 episodes of no atrial fibrillation, including normal sinus rhythm as well as other cardiac arrhythmias. These numbers correspond to a sensitivity of 99.1% and a specificity of 88.3%. |
Year | Venue | Keywords |
|---|---|---|
2009 | BIOSIGNALS 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING | Atrial fibrillation,Atrial flutter,Automatic detection,Mobile device,Tachogram,Morphological filters |
Field | DocType | Citations |
Atrial fibrillation,Computer vision,Computer science,Flutter,Mobile device,Artificial intelligence | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefanie Kaiser | 1 | 0 | 0.68 |
| Malte Kirst | 2 | 5 | 2.61 |
| Christophe Kunze | 3 | 20 | 7.42 |