Key result
The proposed methodology combining Savitzky-Golay filtering and Discrete Wavelet Transform achieved an accuracy of over 90% for R-peak detection in ECG signals, outperforming other methods.
Why the study?
Recorded ECG signals are affected by noises and distortions that lower SNR and can lead to incorrect study and improper diagnosis of heart conditions.
A novel wavelet transform technique combining Savitzky-Golay filtering and DWT improves ECG denoising and R-peak detection compared to standard methods.
ECG noise may impair diagnosis; leaves open whether denoising improves clinical outcomes.
An electrocardiogram (ECG) is a continuous electrical signal from the heart that is recorded to understand the activity and condition of the heart. A recorded ECG signal always follows a defined pattern for a normal heart condition. Variation in the normal ECG pattern can be seen in cases of numerous cardiac abnormalities. A recorded ECG is also affected by a number of noises and distortions, resulting in a low SNR. A variation in ECG pattern can lead to incorrect study and improper diagnosis of heart condition. Thus, to perform an efficient analysis, it is necessary to preprocess the ECG waveform. ECG preprocessing requires noise removal and analysis of necessary features needed to study cardiac activity. In this paper, ECG preprocessing is evaluated by using two noise removal techniques, i.e., finite and infinite impulse response. After this, the R-peaks are detected using discrete wavelet transform (DWT), maximal optimal DWT, principal component analysis and independent component analysis. A wavelet transform technique is further proposed using Savitzky-Golay filtering and DWT. The results obtained from the proposed methodology represent the best results compared to those of other methods explicated in this paper.
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Chhabra et al. (2023) studied ECG signal noise (n=27). Savitzky-Golay filter combined with Discrete Wavelet Transform (DWT) vs. FIR, IIR, DWT, MODWT, PCA, and ICA methods was evaluated on Accuracy of R-peak detection. The proposed methodology combining Savitzky-Golay filtering and Discrete Wavelet Transform achieved an accuracy of over 90% for R-peak detection in ECG signals, outperforming other methods.
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