1. Multi-resolution Analysis TFDs, Wavelets Etc. PCG applications

2. Heart Sound Introduction

3. Recording PCG

4. S2 signal Occurs because of blood flow and closure of Aortic and Pulmonary valves. Is composed of two sub signals A2 – created because of Aortic valve closure P2 - created because of Pulmonary valve closure A2 is characterized with lower frequencies than P2 and is usually precedes it in time.

5. FT – Fourier Transform Fourier Transform returns the frequency components of the signal globaly. For example: S2 signal filtered in [20,120]

6. FT – Fourier Transform The corresponding FT: What does this give us? No Temporal info!

7. Short Time FT for changing signals FT windowed: Window size 64Window size 128Window size 256

8. Short Time FT for changing signals Uncertainty Principle Each window N samples. N/2 coefficients signifying 0-fs/2 frequencies. Space between coefficients

9. Multi-Resolution Analysis

10. Wavelet Transform - Intro Basis functions are compact in time and frequency. Basis function are created basic function called “Mother Wavelet”

11. Wavelet Transform - Intro Basis function are created from mother wavelet through scaling and shifting

12. Wavelet Transform CTW Discrete

13. Wavelet Transform – PCG applications Obaidat M.S., J. Med. Eng. Tech., 1993 Used wavelet transform for HS analysis:

14. Wavelet Transform – PCG applications Reed T.R et al. Proceeding Signal and Image Processing -2005 Used Wavelet decomposition and reconstruction for PCA feature extraction and segmentation to Diastolic and systolic parts

15. Wavelet Transform – PCG applications Liang, H. Hartimo, I. Signal Process. & Comput. Technol. Lab., Helsinki Univ. of Technol., Espoo Used Wavelet Decomposition and Reconstruction of PCG as input to an ANN for study of murmurs. There are several other works doing the same for detection of different HS conditions

16. Wavelet Transform - Applications Image Analysis: Feature Extraction Wavelet and Fractal connection – Self similarity

17. S-Transform CTW with mother wavelet: Properties: Not Orthogonal Directly invertible into the Fourier Transform Spectrum

18. S-Transform – PCG Application G Livanos*, N Ranganatha, J Jiang, Computers in Cardiology 2000. Showed that S-Transform can perform best for the needs of a user who needs a simple and clear display of intensity, frequency and timing, in comparison to Morlet wavelet and STFT.

19. Mathematical definition: Valuable: because of preserving FT essence: Is always pure real Wigner-Ville Distribution

20. Problematic: Cross components unlimited

21. Wigner-Ville Distribution – PCG Applications Xu, Durand et al, IEEE transactions on biomedical engineering 2000, used WVD to extract A2 and P2 from S2 signals and used this to estimate A2-P2 interval

22. Wigner-Ville Distribution – PCG Applications Seedahamed S.M. et al, Biomedical Signal Processing and control (Feb 2006). Use WVD to estimate IF (instantaneous frequency).

23. Chirplet Transform Instead of wavelet basis function that can be scaled and shifted Chirplet Transform uses basis functions that derive for chirps where the phase changes too.

24. Chirplet Transform - Applications O’Neill J.C. et al gave and algorithm to create sparse representation of signal using max likelihood estimation of chirplets

25. Chirplet Transform - Applications

26. My work Currently trying to use TFDs and wavelet transform to extract interval time of A2-P2. Currently working on using S-Transform for basis for a feature extraction algorithm