Detection of ECG Signal: A Survey

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Research areas:
Year:
2013
Type of Publication:
Article
Keywords:
ECG, Fuzzy Logic Methods, P-QRS-T, Discrete Wavelet Transform
Authors:
Prof. M. N. Zade; Prof. P. M. Palkar; Prof. P. N. Aerkewar; Prof. A. S. Pathan
Journal:
IJAIM
Volume:
1
Number:
5
Pages:
126-130
Month:
March
ISSN:
2320-5121
Abstract:
The ECG is nothing but the recording of the heart’s electrical activity.ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. One cardiac cycle in an ECG signal consists of the P-QRS-T waves. This feature extraction scheme determines the amplitudes and intervals in the ECG signal for subsequent analysis. The amplitudes and intervals value of P-QRS-T segment determines the functioning of heart of every human. Recently, numerous research and techniques have been developed for analyzing the ECG signal. The proposed schemes were mostly based on Fuzzy Logic Methods, Artificial Neural Networks (ANN), Genetic Algorithm(GA), Support Vector Machines (SVM), and other Signal Analysis techniques. All these techniques and algorithms have their advantages and limitations. This proposed paper discusses various techniques and transformations proposed earlier in literature for extracting feature from an ECG signal. In addition this paper also provides a comparative study of various methods proposed by researchers in extracting the feature from ECG signal.
Full text: IJAIM_105 Final.pdf

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