http://www.cnr.it/ontology/cnr/individuo/prodotto/ID81303
Validation of a novel algorithm for ventricular repolarization analysis: Use of physionet resources (Contributo in atti di convegno)
- Type
- Label
- Validation of a novel algorithm for ventricular repolarization analysis: Use of physionet resources (Contributo in atti di convegno) (literal)
- Anno
- 2003-01-01T00:00:00+01:00 (literal)
- Alternative label
Cantini, Federico; Emdin, Michele; Passino, Claudio Sanna; Varanini, Maurizio; Conforti, Fabrizio (2003)
Validation of a novel algorithm for ventricular repolarization analysis: Use of physionet resources
in IEEE Computers in Cardiology 2003, Tessoniki, Grecia, 2003
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Cantini, Federico; Emdin, Michele; Passino, Claudio Sanna; Varanini, Maurizio; Conforti, Fabrizio (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.scopus.com/record/display.url?eid=2-s2.0-4143126827&origin=inward (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Rivista
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Istituto di Fisiologia Clinica del CNR (literal)
- Titolo
- Validation of a novel algorithm for ventricular repolarization analysis: Use of physionet resources (literal)
- Abstract
- Ventricular repolarization analysis allows extraction from the ECG signal of quantitative indexes (namely the QT interval), of prognostic value in unselected populations and cardiac patients, being related with arrhythmic risk. Several attempts to improve automatic ECG waveform detection have been accomplished, using signal derivatives, digital filtering, wavelet analysis, neural network techniques, nonlinear approaches. In the present study, a single-lead low-pass differentiation detector of ECG significant points (PulseMeter) has been evaluated. The algorithm performance has been validated against the manual annotation of the \"QT database\" (http://www.physionet.org/), developed for validation purposes. QRS complex and other ECG waveform boundaries were independently evaluated in the present study. The mean values and standard deviations computed improve the result of automatic annotation in QT database, especially in T wave detection. The QRS detector has a sensitivity of 99.96% and a positive predictivity of 99.96% on the first lead and a sensitivity of 99.90% and a positive predictivity of 99.94% on the second lead, showing a better performance than the automatic annotation in the QT database. (literal)
- Prodotto di
- Autore CNR
Incoming links:
- Prodotto
- Autore CNR di
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi