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1.
Journal of Biomedical Engineering ; (6): 263-268, 2015.
Article in Chinese | WPRIM | ID: wpr-266689

ABSTRACT

We proposed a research of a heart sound envelope extraction system in this paper. The system was implemented on LabVIEW based on the Hilbert-Huang transform (HHT). We firstly used the sound card to collect the heart sound, and then implemented the complete system program of signal acquisition, pretreatment and envelope extraction on LabVIEW based on the theory of HHT. Finally, we used a case to prove that the system could collect heart sound, preprocess and extract the envelope easily. The system was better to retain and show the characteristics of heart sound envelope, and its program and methods were important to other researches, such as those on the vibration and voice, etc.


Subject(s)
Humans , Heart Sounds , Signal Processing, Computer-Assisted
2.
Journal of Biomedical Engineering ; (6): 740-772, 2015.
Article in Chinese | WPRIM | ID: wpr-359574

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.


Subject(s)
Humans , Algorithms , Fetal Heart , Physiology , Heart Sounds , Signal Processing, Computer-Assisted , Signal-To-Noise Ratio , Wavelet Analysis
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