Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F14%3A00219399" target="_blank" >RIV/68407700:21220/14:00219399 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/IS3C.2014.324" target="_blank" >https://doi.org/10.1109/IS3C.2014.324</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IS3C.2014.324" target="_blank" >10.1109/IS3C.2014.324</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals
Original language description
This paper presents a novel approach for QRS complex detection and extraction of electrocardiogram signals for different types of arrhythmias. Firstly, the ECG signal is filtered by a band pass filter, and then it is differentiated. After that, the Hilbert transform and the adaptive threshold technique are applied for QRS detection. Finally, the Principal Component Analysis is implemented to extract features from the ECG signal. Nineteen different records from the MIT-BIH arrhythmia database have been used to test the proposed method. A 96.28% of sensitivity and a 99.71% of positive predictivity are reported in this testing for QRS complexity detection, being a positive result in comparison with recent researches.
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
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals
ISBN
978-1-4799-5277-9
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1253-1258
Publisher name
IEEE Computer Society Washington
Place of publication
Washington, DC
Event location
Taichung
Event date
Jun 10, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000366660900312