Clustering Of Ecg Cycles
Loading...
Date
2020
Authors
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract
The paper deals with application of cluster analysis to different ECG records in order to identify particular cardiac pathologies. The work is mainly focused on the detection of premature atrial and premature ventricular beats. Presented approach is based on the signal correlation and further beat type identification and beats clustering via specific ECG features and detection rules, including fuzzy expert rules. By evaluation the method on test data, we obtained Se 76,0 %, Sp 90,2 %, F1 43,8 %, Acc 89,5 %, and PPV 31,1 %. Pure F1 and PPV is due to high number of false positive detections mainly in noisy ECG or ECG with manifested atrial fibrillation.
Description
Citation
Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 121-124. ISBN 978-80-214-5867-3
https://conf.feec.vutbr.cz/eeict/EEICT2020
https://conf.feec.vutbr.cz/eeict/EEICT2020
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
cs
Study field
Comittee
Date of acceptance
Defence
Result of defence
Document licence
© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií