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Communication Dans Un Congrès Année : 2016

Electrocardiogram Signal Analysing

Résumé

In this paper, we develop a new approach based on nonlinear filtering scheme (NLFS) on cardiac signal to evaluate a robust single-lead electrocardiogram (ECG) delineation system and waves localization method based on nonlinear filtering approach. This system is built in two phases, in the first phase, we proposed a mathematical model for detecting ECG features like QRS complex peak, P and T-waves onsets and ends from noise free of synthetic ECG signal. Later, we develop a theoretical model to obtain real approach for detecting these features from real noisy ECG signals. Our method has been evaluated on electrocardiogram signals of QT-MIT standard database, the QRS peak achieve sensitivity (Se) of 98.88 and a positive productivity (P+) of 98.43. For P-onset, P-end, T-end evaluations, this approach provides Sensitivity (Se) of 75.16, 71, and 90.7 respectively. Mean and standard deviation have been computed for differences between the automatic and manual annotations.
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Dates et versions

hal-01257430 , version 1 (16-01-2016)

Identifiants

  • HAL Id : hal-01257430 , version 1

Citer

Ouadi Beya, Mohamad Mazen Hittawe, Nacira Zegadi, Eric Fauvet, Olivier Laligant. Electrocardiogram Signal Analysing: Delineation and localization of ECG component. Bio-inspired systems and signal processing (Bio-Signal 2016), Feb 2016, roma, Italy. ⟨hal-01257430⟩
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