Classification of Normal and Abnormal ECG signals using Support Vector Machine and Fourier Decomposition Method

2020 ◽  
Author(s):  
Ashish Kumar ◽  
Virender Kumar Mehla ◽  
Harshit Tomar ◽  
Manjeet Kumar ◽  
Rama Komaragiri
Keyword(s):  
Support Vector Machine ◽  
Decomposition Method ◽  
Support Vector ◽  
Fourier Decomposition ◽  
Ecg Signals

CLASSIFICATION OF ARRHYTHMIA IN ELECTROCARDIOGRAM USING EMD BASED FEATURES AND SUPPORT VECTOR MACHINE WITH MARGIN SAMPLING

2013 ◽  
Vol 12 (03) ◽  
pp. 1350015 ◽  
Author(s):  
M. SUCHETHA ◽  
N. KUMARAVEL
Keyword(s):  
Support Vector Machine ◽  
Information Source ◽  
Support Vector ◽  
Intrinsic Mode Functions ◽  
Ecg Signals ◽  
Electrocardiogram Signals ◽  
Mode Decomposition ◽  
Computer Based ◽  
Value Decomposition

Electrocardiogram (ECG) signals represent a useful information source about the rhythm and the functioning of the heart. Any disturbance in the heart's normal rhythmic contraction is called an arrhythmia. Analysis of Electrocardiogram signals is the most effective available method for diagnosing cardiac arrhythmias. Computer based classification of ECG provides higher accuracy and offer a potential of an affordable cardiac abnormality mass screening. The empirical mode decomposition is performed on various arrhythmia signals and different levels of intrinsic mode functions (IMF) are obtained. Singular value decomposition (SVD) is used to extract features from the IMF and classification is performed using support vector machine. This method is more efficient for classification of ECG signals and at the same time provides good generalization properties.

Classification of Fatigued Bills Based on a Support Vector Machine by Using the Amplitude Difference Features of Acoustic Signals

2011 ◽  
Vol 131 (8) ◽  
pp. 1495-1501
Author(s):  
Dongshik Kang ◽  
Masaki Higa ◽  
Hayao Miyagi ◽  
Ikugo Mitsui ◽  
Masanobu Fujita ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Acoustic Signals ◽  
Support Vector ◽  
Amplitude Difference

Classification of hyperspectral images based on multifractal features and support vector machine

2018 ◽  
Vol 62 (5) ◽  
pp. 558-562
Author(s):  
Uchaev D.V. ◽  
◽  
Uchaev Dm.V. ◽  
Malinnikov V.A. ◽  
◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Hyperspectral Images ◽  
Support Vector

Color Region Classification of Flue-cured Tobacco Leaves Based on the Image Processing and Support Vector Machine

2013 ◽  
Vol 38 (2) ◽  
pp. 374-379 ◽  
Author(s):  
Zhi-Li PAN ◽  
Meng QI ◽  
Chun-Yang WEI ◽  
Feng LI ◽  
Shi-Xiang ZHANG ◽  
...  
Keyword(s):  
Image Processing ◽  
Support Vector Machine ◽  
Support Vector ◽  
Tobacco Leaves ◽  
Region Classification
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