IRIS Institutional Research Information System - AIR Archivio Istituzionale della Ricerca
IRIS è il sistema di gestione integrata dei dati della ricerca (persone, progetti, pubblicazioni, attività) adottato dall'Università degli Studi di Milano.
AIR nasce in UNIMI nel 2006 con lo scopo di raccogliere, documentare e conservare le informazioni sulla produzione scientifica dell'Università degli Studi di Milano e costituisce di fatto l'Anagrafe della ricerca dell'Ateneo.
EnglishThis work presents an evolutionary ANN classifier system as an heart beat classification algorithm suitable for implementation on the PhysioNet/Computing in Cardiology Challenge 2011, whose aim is to develop an efficient algorithm able to run within a mobile phone, that can provide useful feedback in the process of acquiring a diagnostically useful 12-lead Electrocardiography (ECG) recording. The method used in such a problem is to apply a very powerful natural computing analysis tool, namely evolutionary neural networks, based on the joint evolution of the topology and the connection weights together with a novel similarity-based crossover. The work focuses on discerning between usable and unusable electrocardiograms tele-medically acquired from mobile embedded devices. A prepropcessing algorithm based on the Discrete Fourier Trasform has been applied before the evolutionary approach in order to extract the ECG feature dataset in the frequency domain. Finally, a series of tests has been carried out in order to evaluate the performance and the accuracy of the classifier system for such a challenge.
Electrocardiographic signal classification with evolutionary artificial neural networks / A. Azzini, M. Dragoni, A.G.B. Tettamanzi - In: Applications of evolutionary computation: EvoApplications 2012 : Málaga, Spain, april 11-13, 2012 : proceedings / [a cura di] C. Di Chio ... [et al.]. - Berlin : Springer, 2012. - ISBN 9783642291777. - pp. 295-304 (( convegno EvoApplications tenutosi a Málaga nel 2012.
| Titolo: | Electrocardiographic signal classification with evolutionary artificial neural networks |
| Autori: | AZZINI, ANTONIA (Primo) TETTAMANZI, ANDREA GIOVANNI BATTISTA (Ultimo) |
| Parole Chiave: | Signal processing ; Heartbeat classification ; Evolutionary algorithms ; Neural networks |
| Settore Scientifico Disciplinare: | Settore INF/01 - Informatica |
| Data di pubblicazione: | 2012 |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-642-29178-4_30 |
| Tipologia: | Book Part (author) |
| Appare nelle tipologie: | 03 - Contributo in volume |
File in questo prodotto:
Copyright © 2021