Denoising ecg with Hilbert Transform

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Andreea Girliceanu
Andreea Girliceanu on 8 May 2013
Answered: HSIN-YUAN CHEN on 26 Jul 2023
Does anyone know how to implement the code for Denoising of Electrocardiogram Signal Based on Hilbert-Huang transform??

Answers (1)

HSIN-YUAN CHEN
HSIN-YUAN CHEN on 26 Jul 2023
Hi,
To denoise Electrocardiogram (ECG) signals using Hilbert-Huang transform (HHT) in MATLAB:
Load your ECG data:
ecg_data = load('your_ecg_data.mat');
Apply Empirical Mode Decomposition (EMD) using a custom function:
imfs = emd(ecg_data);
Denoise the intrinsic mode functions (IMFs) using a threshold:
for i = 1:length(imfs)
if energy(imfs(i)) < threshold
imfs(i) = 0;
end
end
Reconstruct the denoised ECG signal:
denoised_ecg = sum(imfs);
Apply Hilbert Transform:
analytic_signal = hilbert(denoised_ecg);
This outline is simplified, and you may need to adapt it according to your specific needs and data.
  1. MATLAB does not provide a built-in emd function, so you'll need to source this elsewhere.
  2. The threshold used in step 3 may need to be adjusted according to the specific needs and data2.
  3. The hilbert function in MATLAB returns the analytic signal, not the Hilbert spectrum.
  4. Note that the energy function is not a built-in MATLAB function, so you'll need to define it yourself or use a different method to calculate the energy of the IMFs.

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