Original title: Clustering Of Ecg Cycles
Authors: Němečková, Karolína
Document type: Papers
Language: cze
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.
Keywords: cardiac beats clustering; ECG correlation; extrasystols detection; fuzzy inference system
Host item entry: Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers, ISBN 978-80-214-5867-3

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/200537

Permalink: http://www.nusl.cz/ntk/nusl-447589


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers