DocumentCode :
674560
Title :
A Noise-Adaptive Method for Detection of Brief Episodes of Paroxysmal Atrial Fibrillation
Author :
Petrenas, Andrius ; Sornmo, Leif ; Marozas, Vaidotas ; Lukosevicius, A.
Author_Institution :
Biomed. Eng. Inst., Kaunas Univ. of Technol., Kaunas, Lithuania
fYear :
2013
fDate :
22-25 Sept. 2013
Firstpage :
739
Lastpage :
742
Abstract :
The aim of this work is to develop a method for detection of brief episode paroxysmal atrial fibrillation (PAF). The proposed method utilizes four different features: RR interval irregularity, absence of P waves, presence of f-waves and noise level. The obtained features are applied to the Mamdani-type fuzzy inference method for decision-making. The performance was evaluated on one hundred 90 s long surrogate ECG signals with brief PAF episodes (5-30 beats). The robustness to noise in ECGs where noise level in each set is incremented in steps of 0.01 mV from 0 to 0.2 mV was examined as well. When compared to the coefficient of sample entropy, our method showed considerably better performance for low and moderate noise levels (<; 0.06 mV) with an area under the receiver operating characteristic curve of 0.9 and 0.94, respectively. Similar performance is expected for higher noise levels as atrial activity is less used in the detection process. Finally, the results suggest that our method is more robust to false alarms due to ectopic beats or other irregular rhythms than the method under comparison.
Keywords :
decision making; diseases; electrocardiography; entropy; feature extraction; fuzzy reasoning; medical signal detection; medical signal processing; noise; sensitivity analysis; Mamdani-type fuzzy inference method; P waves absence feature; RR interval irregularity feature; area under the receiver operating characteristic curve; atrial activity; brief PAF episodes; brief paroxysmal atrial fibrillation episodes detection; decision making; ectopic beats; f-waves presence feature; false alarms; noise level feature; noise-adaptive method; robustness; sample entropy coefficient; surrogate ECG signal; time 90 s; Abstracts; Estimation; Spatiotemporal phenomena; Time-frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology Conference (CinC), 2013
Conference_Location :
Zaragoza
ISSN :
2325-8861
Print_ISBN :
978-1-4799-0884-4
Type :
conf
Filename :
6713483
Link To Document :
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