DocumentCode :
3673142
Title :
Fast fourier transform for feature extraction and neural network for classification of electrocardiogram signals
Author :
Martina Mironovova;Jir? B?la
Author_Institution :
Department of Instrumentation and Control Czech Technical University in Prague, Faculty of Mechanical Engineering Prague, Czech Republic
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a novel approach to complex classification of heart abnormalities registered by electrocardiogram signals. It uses a combined approach of a Fast Fourier Technique for signal filtering and R-peaks detection and heart rate extraction, followed by signal modelling and classification by neural network based on recording of ECG. Obtained information is processed together for a complex evaluation of the signal in time.
Keywords :
"Electrocardiography","Neural networks","Databases","Heart rate variability","Heart beat"
Publisher :
ieee
Conference_Titel :
Future Generation Communication Technology (FGCT), 2015 Fourth International Conference on
ISSN :
2377-262X
Electronic_ISBN :
2377-2638
Type :
conf
DOI :
10.1109/FGCT.2015.7300244
Filename :
7300244
Link To Document :
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