Isolation of Informative Features for the Analysis of QRS Complex in ECG Signals

Pashko, Anatolii; Krak, Iurii; Stelia, Oleg; Khorozov, Oleg

doi:10.1007/978-3-030-54215-3_26

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…A new method is proposed for removing baseline drift from the ECG signal based on authors results on ECG investigation [10][11][12][13]17]. The method is based on the use of a sliding window containing 5 points.…”

Section: Using Spline Functions For Elimination the Baseline Wandermentioning

confidence: 99%

Baseline Wander Correction of the Electrocardiogram Signals for Effective Preprocessing

Pashko

Krak²,

Stelia³

et al. 2021

Lecture Notes in Computational Intelligence and Decision Making

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Thus, to effectively solve the problem of eliminating the ECG baseline drift, it is necessary to filter the ECG signal. In this study for solve the problem of eliminating the ECG baseline drift, various filters were used: a low-pass filters based on the forward and inverse discrete Fourier transform, Butterworth filter, median filter, Savitsky-Golay filter. The results obtained confirmed the efficiency of filtering harmonic noise based on forward and backward DFT on real data. The method makes it possible to implement a narrow-band stop filter in the range from 0 to the Nyquist frequency. In this case, the notch band can be less than 0.1% of the Nyquist frequency, which is important when processing ECG signals.The filtering result was evaluated by the appearance of the filtered ECG. The evaluation criterion was the presence on the signal of characteristic fragments reflecting the work of the atria and ventricles of the heart in the form of a P wave, a QRS complex and a ST-T segment. A new method has been developed for filtering the ECG signal, which is based on the use of a sliding window containing 5 points. A linear function is constructed from a sample of five points using the least squares method. The value of the resulting linear function at the midpoint is used as the new value. Several iterations are performed to achieve a good result. To eliminate the baseline drift for the ECG fragment, it is proposed to use a special cubic interpolation spline. The algorithm for constructing the used spline requires solving a system of equations with a tridiagonal matrix.

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Section: Using Spline Functions For Elimination the Baseline Wandermentioning

confidence: 99%

Baseline Wander Correction of the Electrocardiogram Signals for Effective Preprocessing

Pashko

Krak²,

Stelia³

et al. 2021

Lecture Notes in Computational Intelligence and Decision Making

Self Cite

View full text Add to dashboard Cite

show abstract

Signal Quality Evaluation and Processing for QRS Detection in ECG based Smart Healthcare Systems

Singh

Akram

Sivakumar

et al. 2022

2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)

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Isolation of Informative Features for the Analysis of QRS Complex in ECG Signals

Cited by 2 publications

References 12 publications

Baseline Wander Correction of the Electrocardiogram Signals for Effective Preprocessing

Baseline Wander Correction of the Electrocardiogram Signals for Effective Preprocessing

Signal Quality Evaluation and Processing for QRS Detection in ECG based Smart Healthcare Systems

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