Adaptive Threshold, Wavelet and Hilbert Transform for QRS Detection in Electrocardiogram Signals
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F17%3A00315465" target="_blank" >RIV/68407700:21220/17:00315465 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-69835-9_73" target="_blank" >http://dx.doi.org/10.1007/978-3-319-69835-9_73</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-69835-9_73" target="_blank" >10.1007/978-3-319-69835-9_73</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive Threshold, Wavelet and Hilbert Transform for QRS Detection in Electrocardiogram Signals
Original language description
This paper combines Hilbert and Wavelet transforms and an adaptive threshold technique to detect the QRS complex of electrocardiogram signals. The method is performed in a window framework. First, the Wavelet transform is applied to the ECG signal to remove noise. Next, the Hilbert transform is applied to detect dominant peak points in the signal. Finally, the adaptive threshold technique is applied to detect R-peaks, Q, and S points. The performance of the algorithm is evaluated against the MIT-BIH arrhythmia database, and the numerical results indicated significant detection accuracy.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 12th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2017)
ISBN
978-3-319-69835-9
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
777-786
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Barcelona
Event date
Nov 8, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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