Unsupervised classification of atrial heartbeats using a prematurity index and wave morphology features.
ECG heartbeat type detection and classification are regarded as important procedures since they can significantly help to provide an accurate automated diagnosis. This paper addresses the specific problem of detecting atrial premature beats, that had been demonstrated to be a marker for stroke risk...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 47; no. 7; pp. 731 - 742 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jul2009
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| Acceso en línea: | Ver este registro en EBSCOhost |