Denoising of Fetal Heart Sound Based on Empirical Mode Decomposition Method.
- Author:
Qiaoqiao LIU
;
Zhixiang TAN
;
Yi ZHANG
;
Hua WANG
- Publication Type:Journal Article
- MeSH:
Algorithms;
Fetal Heart;
physiology;
Heart Sounds;
Humans;
Signal Processing, Computer-Assisted;
Signal-To-Noise Ratio;
Wavelet Analysis
- From:
Journal of Biomedical Engineering
2015;32(4):740-772
- CountryChina
- Language:Chinese
-
Abstract:
Fetal heart sound is nonlinear and non-stationary, which contains a lot of noise when it is colleced, so the denoising method is important. We proposed a new denoising method in our study. Firstly, we chose the preprocessing of low-pass filter with a cutoff frequency of 200 Hz and the resampling. Secondly, we decomposed the signal based on empirical mode decomposition method (EMD) of Hilbert-Huang transform, then denoised some selected target components with wavelet soft threshold adaptive noise cancellation algorithm. Finally we got the clean fetal heart sound by combining the target components. In the EMD, we used a mask signal to eliminate the mode mixing problem, used mirroring extension method to eliminate the end effect, and referenced the stopping rule from the research of Rilling. This method eliminated the baseline drift and noise at once. To compare with wavelet transform (WT), mathematical morphology (MM) and the Fourier transform (FT), the SNR was improved obviously, and the RMSE was the minimum, which could satisfy the need of the practical application.
