DocumentCode :
1568302
Title :
R wave detection using Coiflets wavelets
Author :
Elgendi, Mohamed ; Jonkman, Mirjam ; De Boer, Friso
Author_Institution :
Sch. of Eng. & Inf. Technol., Charles Darwin Univ., Darwin, NT
fYear :
2009
Firstpage :
1
Lastpage :
2
Abstract :
Accurate detection of QRS complexes is important for ECG signal analysis. In this paper, a generic algorithm using Coiflet wavelets is introduced to improve the detection of QRS complexes in arrhythmia ECG Signals that suffer from: 1) non-stationary effects, 2) low signal-to-noise ratio, 3) negative QRS polarities, 4) low QRS amplitudes, and 5) ventricular ectopics. The algorithm achieves high detection rates by using a signal-to-noise ratio threshold instead of predetermined static thresholds. The performance of the algorithm was tested on 48 records of the MIT/BIH Arrhythmia Database. It was shown that this adaptive approach results in accurate detection of the QRS complex and that Coiflet1 achieves better detection rate than the other Coiflet wavelets.
Keywords :
adaptive signal detection; bioelectric phenomena; electrocardiography; medical signal detection; wavelet transforms; Coiflets wavelets; MIT-BIH Arrhythmia ECG Database; QRS complex detection; R wave detection; adaptive detection; arrhythmia ECG signal analysis; generic algorithm; nonstationary effects; signal-to-noise ratio threshold; ventricular ectopics; Databases; Discrete wavelet transforms; Electrocardiography; Frequency; Heart rate detection; Heart rate variability; Information technology; Signal analysis; Signal to noise ratio; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioengineering Conference, 2009 IEEE 35th Annual Northeast
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4362-8
Electronic_ISBN :
978-1-4244-4364-2
Type :
conf
DOI :
10.1109/NEBC.2009.4967756
Filename :
4967756
Link To Document :
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