Comparison of Wavelet Types and Thresholding Methods on Wavelet Based Denoising of Heart Sounds

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(a)

(b)

Figure 3. The SNR values after denoising before denoising

for level 5 and 8.

(a) (b)

(c) (d)

Figure 4. The denoised signal using four different threshold

rules at eighth level.

4. Conclusions

The wavelet denoising techniques were studied on a

noised PCG signal in this work. The performances of

several variations of denoising including thresholding

rules and the type of wavelet were compared to produce

the best denoising results of the methods.

We conclude that reasonable decomposition level is

bsolutely depending on the sampling frequency and the

frequency band of the signal. Just in this study, the de-

composition level of 5 produced reasonable results be-

cause the frequency band of a normal PCG signal is

around 150 - 200 Hz and the sampling frequency is 11.5

KHz. Since the noise level method is one of the impor-

tant parameter in wavelet denoising, it is examined for

different levels. We have not seen any noteworthy dif-

ferences in the methods from level 1 to level 6. After this

level, rigresure method has showed superiority to the

other methods in terms of SNR level. Consequently, it is

determined that the wavelet type is not very important if

the oscillation number is not very low, th e decomposition

level is absolutely depends on the frequency band of the

PCG signal and its sampling frequency, and rigresure

method is best of the noise estimation techniques.

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