Key result
FFT maximizes signal-to-noise ratio for denoising ECG apnea signals while DWT optimizes visual reconstruction.
Why the study?
Heart abnormalities dominate globally, requiring noise-free ECG signals, but noise in RR intervals during apnea makes the QRS complex difficult to identify.
The Fast Fourier transform method is superior to the Discrete Wavelet Transform method for improving the signal-to-noise ratio in ECG apnea signal denoising.
May favor FFT for SNR in ECG denoising; leaves open clinical validation before practice adoption.
An Electrocardiogram (ECG) signal results from recording the heart's electrical activity. Currently, diseases originating from heart abnormalities still dominate the world. Therefore, doctors need to find an ECG signal that is free from noise, this cleaning process is called denoising. The denoising methods commonly used are the wavelet transform method, and the Fourier transform method. Testing was conducted on ECG signal data with abnormalities in Apnea with RR intervals filled with noise, making the QRS complex difficult to identify. As a result, the Discrete Wavelet Transform (DWT) method produces the best form of reconstruction, resembling the initial ECG signal, while the Fast Fourier transform (FFT) method produces the best signal-to-noise ratio (SNR) for the denoising process. So, we get a superior FFT method in the ECG signal denoising process.
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Aini et al. (2023) studied Apnea. Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) vs. Raw ECG signal was evaluated on Signal to Noise Ratio (SNR). The Fast Fourier Transform (FFT) method produced the best signal-to-noise ratio for denoising ECG apnea signals, while the Discrete Wavelet Transform (DWT) method provided the best visual reconstruction.
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