On the choice of the wavelets for ECG data compression

Besar, Rosli; Eswaran, C.; Sahib, S. Khalsa; Simpson, R. J.

doi:10.1109/icassp.2000.860184

Cited by 19 publications

(13 citation statements)

References 7 publications

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“…A família Daubechies foi escolhida por ser indicada como a melhor wavelet para comprimir sinais de ECG conforme [19], uma vez que se utiliza para efetuar a extração de características. As demais famílias foram escolhidas para efetuar uma comparação dentre as famílias e suas respectivas ordens.…”

Section: Materiais E Métodosunclassified

Detecção de Cardiopatias por Eletrocardiograma Utilizando Redes Neurais Artificiais

Suterio¹,

Agulhari²,

Spatti³

2018

Anais Do v Congresso Brasileiro De Eletromiografia E Cinesiologia E X Simpósio De Engenharia Biomédica

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Resumo: Este artigo consiste em propor um algoritmo para auxiliar o profissional da saúde, visando facilitar a interpretação do eletrocardiograma (ECG) de pacientes para a detecção de arritmias entre ECGs de pacientes saudáveis e com cardiopatia. O algoritmo utiliza da transformada wavelet packet (TWP) para a extração de características dos ECGs e os dados obtidos, após a extração de características, são apresentados para um algoritmo, multilayer perceptron (MLP)

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Section: Materiais E Métodosunclassified

Detecção de Cardiopatias por Eletrocardiograma Utilizando Redes Neurais Artificiais

Suterio¹,

Agulhari²,

Spatti³

2018

Anais Do v Congresso Brasileiro De Eletromiografia E Cinesiologia E X Simpósio De Engenharia Biomédica

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“…For obtaining effective and efficient data compression, the choice of different analysis -synthesis filter pairs, corresponding to different wavelet bases, is especially significant. [18]. In realization, the number of decompositions, frame size and filter pair need to be selected suitably.…”

Section: Wavelet Transformmentioning

confidence: 99%

Modified SPIHT wavelet compression for ECG signal

Singh

Kumar

Saxena

2007

Journal of Medical Engineering & Technology

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This paper presents a modified version of Set Partitioning In Hierarchical Trees (SPIHT) wavelet compression method, which has been developed for ECG signal compression. Two more steps in the existing technique have been added to achieve higher compression ratio (CR) and lower percentage rms difference (PRD). The method has been tested on selected records from the MIT-BIH arrhythmia database. Even with two more steps, the method retains its simplicity, computational efficiency and self-adaptiveness, without compromising on any other performance parameter.

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“…• Transform methods, which first transform the signal to another time-frequency representation better suited for detecting and removing redundancies [3], [4], [5], [9], [14], [17], [18] and [19].…”

Section: Introductionmentioning

confidence: 99%

“…The ECGs are almost periodic consisting of cardiac beat pulses with periods of approximately one second. The efficiency of ECG compression using wavelets depends on the shape of the wavelet, motivating a series of researches on the choice of different waveforms for this technique [4], [9], [14], [19] and [21].…”

Section: Introductionmentioning

confidence: 99%

Compressing electrocardiogram signals using parameterized wavelets

Agulhari

Bonatti

2008

Proceedings of the 2008 ACM Symposium on Applied Computing

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A compression method, based on the choice of a wavelet that matches the electrocardiogram signal to be compressed, is proposed in this paper. The scaling filter that minimizes the distortion of the compressed signal are used to determine the wavelet. The scaling filter is used to generate the coefficients of projection of the ECG signal in the scaling and wavelet subspaces, and only the most significant coefficients are retained. Coding methods are applied to the retained coefficients in order to improve the compression.

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On the choice of the wavelets for ECG data compression

Cited by 19 publications

References 7 publications

Detecção de Cardiopatias por Eletrocardiograma Utilizando Redes Neurais Artificiais

Detecção de Cardiopatias por Eletrocardiograma Utilizando Redes Neurais Artificiais

Modified SPIHT wavelet compression for ECG signal

Compressing electrocardiogram signals using parameterized wavelets

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