A Hybrid-Elliptic-Notch-Savitzky–Golay Filter Approach for Enhanced ECG Signal Denoising
DOI:
https://doi.org/10.22153/kej.2026.05.001Keywords:
Baseline wander; distorting; electrocardiogram; electromyogram; power line interference; noise reductionAbstract
One of the most important testing tools for the assessment and diagnosis of cardiovascular diseases is the electrocardiogram (ECG) signal. However, the ECG signal is very sensitive to different types of noise, such as baseline drift, powerline interference and electromyogram (EMG) noise. Therefore, these noises need to be removed from the ECG signals due to their significance in detection and diagnosis of cardiovascular disease. In this paper, a novel method for simultaneously removing these different types of noise from the ECG signals by using a hybrid filtering framework is proposed. This hybrid approach assures efficient noise reduction, and the integrity of the ECG signal is preserved for accurate diagnosis. The proposed method consists of two stages. In the initial stage, the three filters that make up the hybrid filtering are applied: an elliptic high-pass filter to remove the baseline wander, a notch filter to reduce the 50/60 Hz power line interference and a Savitzky–Golay filter to reduce the high-frequency EMG noise. Second, the preprocessed ECG signal is divided into segments of different durations by segmentation to facilitate practical analysis and feature extraction in later stages. The effectiveness of the proposed method is shown by the tests and proven results using MATLAB R2023a. The method is evaluated using a large collection of real ECG signals from the MIT-BIH arrhythmia database. The proposed method outperforms other methods in signal-to-noise ratio (39.10 dB) and mean square error (0.06014*10⁻³); it can remove different types of noise without distorting the ECG signal characteristics. The study’s contribution to reliable noise removal of ECG signals for clinical applications is significant.
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