Tag electrocardiogram [8 articles]

Abstract

Denoising of electrocardiogram (ECG) is the fundamental technique for manual or automatic ECG diagnosis. Model-based denoising has attracted initial studies since the ECG dynamical model was established in 2003 and been demonstrated to outperform most model-less denoising methods. The focus of this paper is robust denoising of abnormal ECG signals, which do not satisfy the assumption in previous model-based studies that morphological or physiological variations are small from one beat to another. A mean shift based initializer is proposed to provide ...

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Time–frequency representations are commonly used to analyze the oscillatory nature of brain signals in EEG, MEG or intracranial EEG. In the signal processing literature, there is growing interest in sparse time–frequency representations, where the data are described using few components. A popular algorithm is Matching Pursuit (MP) [Mallat SG, Zhang Z. Matching pursuits with time–frequency dictionaries. IEEE Trans Sig Proc 1993;41:3397–415], which iteratively subtracts from the signal its projection on atoms selected from a dictionary. The MP algorithm was recently adapted ...

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We made use of multivariate nonlinear analysis methods to study the interdependence between the cardiac interval variability and both the respiratory activity and the systolic pressure in rats. The study was carried out in basal conditions and after the application of different drugs affecting the cardiovascular system. The results showed that there are changes both in the extent and in the directionality of such interdependences because of the drugs. The inhibition of the NO and the parasympathetic blockade changed the cardiovascular ...

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A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator can specify the mean and standard deviation of the heart rate, the morphology of the PQRST cycle, and the power spectrum of the RR tachogram. In particular, both respiratory sinus arrhythmia at the high frequencies (HFs) and Mayer waves at the low frequencies (LFs) together with the LF/HF ratio are incorporated in the model. Much of the ...

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The wavelet transform has emerged over recent years as a powerful time–frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both ...

Abstract

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Abstract

The performance of different wavelet- and wavelet packet-based methods for removing simulated noise was studied using an electrocardiogram (ECG) signal. A non-linear denoising approach was investigated by applying soft and hard thresholding methods, in which thresholds were chosen using four different methods. Coiflet wavelet and wavelet packet functions were used to build up the dyadic wavelet and optimized wavelet packet decompositions. This study involves the quantitative comparison of different denoising approaches by means of optimized error measures and visual inspection of ...

Abstract

Simulating the electrocardiogram requires specifying the transmembrane potential distribution within the heart and calculating the potential on the surface of the body. Often, such calculations are based on the bidomain model of cardiac tissue. A subtle but fundamental problem arises when considering the boundary between the cardiac tissue and the surrounding volume conductor. In general, one finds that two potentials--the extracellular potential in the tissue and the potential in the surrounding bath--obey three boundary conditions, implying that the potentials are overdetermined. ...