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Result Analysis of Noise Removal in ECG Signal using Wavelet Decomposition Technique
Author(s) -
Anamika Rajput,
Pankaj Soni,
Anshul Awasthi
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017914807
Subject(s) - computer science , wavelet , noise (video) , signal (programming language) , decomposition , speech recognition , pattern recognition (psychology) , artificial intelligence , algorithm , chemistry , organic chemistry , image (mathematics) , programming language
Now-a-days Cardio vascular diseases become huge threat to the lifetime of human beings. ECG is one in all the simplest technique to give clear information about cardiac arrhythmia. The electro-cardiogram may be a technique of recording bioelectric currents generated by the heart that is useful for diagnosing several cardiac diseases. The feature extraction and denoising of ECG are extremely useful in cardiology. ECG may be a non-stationary signal and it is used for the first diagnosis of cardiac abnormalities like arrhythmia, MI and conduction defects. However the ECG signals usually contaminated by different noises. The ECG signal should be denoised to remove all the noises like Additive White Gaussian noises. In latest years, electro-cardiogram (ECG) acting a commanding role in heart illness diagnostics, Human pc Interface (HCI), stresses and emotional states valuation, etc. Generally, ECG signals exaggerated by noises like baseline wandering, power line interference, electromagnetic intervention, and high frequency noises throughout information acquirement.

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