A method for arrhythmic episode classification in ECGs using fuzzy logic and Markov models
| dc.contributor.author | Tsipouras, M.G., | en |
| dc.contributor.author | Goletsis, Y., | en |
| dc.contributor.author | Fotiadis, D.I. | en |
| dc.date.accessioned | 2015-11-24T17:05:19Z | |
| dc.date.available | 2015-11-24T17:05:19Z | |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11299 | |
| dc.rights | Default Licence | - |
| dc.title | A method for arrhythmic episode classification in ECGs using fuzzy logic and Markov models | en |
| heal.abstract | A merhod for arrhythmic episode classification using only the RR-interval signal is presented. The merhod is based on f u m logic and Markov models, while Classification is performed for nine categories of cardiac rhythms. A two-stage classifier is applied. In the first stage, a fuuy system clussiQies the episode using the mean value and standard deviaiion of the KR-intervals. In the second, the RR-interval signal is transformed to character sequences, which are classified by Markov models. Two representation techniques are used for the extraction of the characrer sequences: symbolic dynamics and one bused on the ER-interval length. The classification of an episode is achieved combining the outcomes of the two stages. The MIT-BIH arrhythmia database is used for the evaluation of the proposed method. The obtained results indicate high perlformance (accuracy 73%) in arrhythmic episode classijicafion. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.journalName | Computers in Cardiology | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2004 | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημών | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
Αρχεία
Φάκελος/Πακέτο αδειών
1 - 1 of 1
Φόρτωση...
- Ονομα:
- license.txt
- Μέγεθος:
- 1.74 KB
- Μορφότυπο:
- Item-specific license agreed upon to submission
- Περιγραφή: