Electrocardiogram Signal Analysing

Ouadi Beya (1) , Mohamad Mazen Hittawe (1) , Nacira Zegadi , Eric Fauvet (1) , Olivier Laligant (1)

1 Le2i - Laboratoire Electronique, Informatique et Image [UMR6306]

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.

Keywords: Signal processing; NFLS; ECG; QRS complex; Waves delineation

Domains: Computer Science [cs]; Signal and Image processing

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⟩