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Electrocardiogram Baseline Wander Removal Using Stationary Wavelet Approximations

12th International Conference on Optimization of Electrical and Electronic Equipment OPTIM 2010. Electrocardiogram Baseline Wander Removal Using Stationary Wavelet Approximations. Beatrice ARVINTI, Dumitru TOADER, Marius COSTACHE, Alexandru ISAR. “Politehnica” University, Timisoara, Romania.

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Electrocardiogram Baseline Wander Removal Using Stationary Wavelet Approximations

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  1. 12th International Conference on Optimization of Electrical and Electronic Equipment OPTIM 2010 Electrocardiogram Baseline Wander Removal Using Stationary Wavelet Approximations Beatrice ARVINTI, Dumitru TOADER, Marius COSTACHE, Alexandru ISAR “Politehnica” University, Timisoara, Romania

  2. Contents • Introduction • Proposed method • Simulation parameters • Simulation results • Conclusion

  3. Objectives • To propose a new method for the correction of the baseline wander of ECGs • To reduce the required computation time • To enhance further development of a non-supervised method

  4. Introduction • In practice, ECG signals are affected by noise Fig.1. “Noisy” ECG signal • Disadvantage: • a wandering of the baseline of the ECG, which can mask significant features • failure of the processing task

  5. Proposed method • Estimation of the “overall tendency” of the ECG through multiresolution analysis (MRA) • Procedure steps: • Estimation of the baseline wander using low-pass filtering • Elimination of the baseline wander by subtraction from the acquired ECG

  6. Baseline’s estimator Corrected ECG SWT dk=0 ISWT + Proposed method • The Stationary Wavelet Transform (SWT) Fig. 2. The architecture of the proposed baseline’s correction system ECG

  7. Proposed method The impulse response of the filter: The frequency response of the used filter: Fig. 3. The scheme of the system that computes the stationary wavelet transform. The systems with the impulse responses hk are low-pass filters and the systems with impulse responses gkare high-pass filters.

  8. Simulation parameters • Parameters: • the mother wavelets used for the computation of the SWT • the first mother wavelets proposed by Ingrid Daubechies: Dau_2 • the sampling frequency of the ECG: 360 Hz • the cut-off frequency: < 1/T • the resolution level K :

  9. Simulation results Best result a) b) Fig 4. First three beats. a) Before treatment (the baseline is represented in red), b) After treatment (the new baseline is represented in green)

  10. Simulation results Worst result Fig. 5. Simulation results obtained for the ECG 103 of the MIT-BIH arrhythmia databasewith the start moment at 18’20’’. a) Original waveform (in blue) and the estimation of the baseline (in red) and b) Result of the compensation method

  11. Conclusion • The proposed method is a non-supervised method • The estimation of the ECG’s baseline is done with the aid of the SWT, computed using the mother wavelets Dau-2 for 8 decomposition levels • The equivalence of the proposed estimation method with a low-pass filtering of the ECG using a special filter • The method works well for ECGs moderately distorted by the drifts of their baseline • The proposed method is robust • Requires less computational effort

  12. THANK YOU FOR YOUR ATTENTION !

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