Key result
Multistage cascaded filtering improves ECG signal-to-noise ratio to ~16 dB over standard filters.
Why the study?
Raw ECG signals contain artifacts such as electromyography interference and baseline drift that need to be removed to obtain the lowest possible noise.
Demonstrates a multistage filtering technique to reduce electromyography noise and baseline drift in ECG recordings, suggesting improved accuracy for cardiac screening systems.
In this paper, a new approach was adopted in order to remove the artifacts present in the raw ECG signal. To realizing this process a multiple types of filters for a variety of types of noises have been applied to obtain the lowest possible noise. Initially, the ECG signal was filtered from the electromyography signal, and then the filtered signal was passed again on another filter for the purpose of removing its drift from the baseline. The effectiveness of the suggested approach has been assessed in comparison to the conventional ECG signal. Results of this study showed significantly less signaling noise than was present in the conventional signal. Overall, the signal to noise ratio and the mean square error of the filtered ECG reached 15.72 and 0.006, respectively, in the filtered signal of one of the ECG recordings.
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M. A. Waheed (2023) studied Electrocardiogram (ECG) signal noise (electromyogram interference and baseline wander) (n=6). Multistage cascaded filter (Butterworth low-pass filter followed by zero-phase-shift filter) vs. Conventional/unfiltered ECG signal, Chebyshev low-pass filter, and cooperative filtering was evaluated on Signal-to-Noise Ratio (SNR) and Mean Square Error (MSE) in record 104m. Multistage cascaded filtering of ECG signals achieved a peak signal-to-noise ratio of 15.72 dB and a mean square error of 0.006, outperforming cooperative (12 dB) and Chebyshev (11.96 dB) filters.
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