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In this paper, a new method of arrhythmia classification is proposed. At first we extract twenty two features from electrocardiogram signal. We propose a novel classification system based on genetic algorithm to improve the generalization performance of the SVM classifier. For this purpose, we have optimized the SVM classifier design by searching for the best value of the parameters that tune its...
This research is on presenting a new approach for cardiac arrhythmia disease classification. The proposed method combines both support vector machine (SVM) and genetic algorithm approaches. First, twenty two features from electrocardiogram signal are extracted. These features are obtained semiautomatically from time-voltage of R, S, T, P, Q features of an Electro Cardiagram signals. Genetic algorithm...
In this paper we present an approach for biometric key generation using wavelets and electrocardiogram (ECG) signals. The stages that comprise the approach are one time enrollment and key derivation. This work is based on the uniqueness and quasi-stationary behavior of ECG signals with respect to an individual. This lets to consider the ECG signal as a biometric characteristic and guarantees that...
In this work, the effect of the electromagnetic radiation generated by mobile phone, on the heart rate variability (HRV) has been investigated using correlation dimension calculation which is a nonlinear analysis method. The 17 volunteer subjects participated to our work and the experiment is designed as three periods and each period have 7 minutes. The electrocardiogram (ECG) signals were recorded...
In this paper a new efficient fractal based compression algorithm is proposed for electrocardiogram signals. The self-similarities in the ECG signals make them suitable to be compressed efficiently using fractal based methods. In the proposed method, as in the basic fractal based compression method, each part of the signal is mapped to another part with a reasonable error. The transformed maps are...
A reversible watermarking algorithm with high data-hiding capacity has been developed for electrocardiogram (ECG) signal based on wavelet transforms. In electrocardiogram signal, the energy is concentrated in QRS complex waves. So the selection of wavelet coefficients for hiding should avoid making QRS complex waves distort obviously. The algorithm hides bits in the expansion of selected coefficients...
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