GRUBU (SIGNALS RECORDING and PATIENTS )
Mechanical heart valves audio signals are received via an electronic stethoscope and ECG signal level electrodes. Electronic stethoscope and transferred to the computer via the interface data acquisition information obtained from surface electrodes. Recording system available from 2013 Altunkaya and other detailed information.
St. Jude brand mitral heart valve replacement was performed two months after shortness of breath, was admitted to hospital with complaints of swelling of the legs of the control patients had echocardiography. Determined by a mitral valve leakage of the patient's complaints and a cardiologist for opening the folding around the mechanical heart valve leakage has been detected echocardiographic results and it was decided to repair the seam .
Mechanical heart repair heart patients has been set up illegally recording two tackles before surgery and 147 were acquired to investigate the sound of the cardiac cycle. At different times of the same patients were re-recorded in a leak repaired four times after surgery and looks were acquired for a total of 96 investigations of cardiac cycle. After two months of general surgery St., sounds were used for the statistical comparison of 98 cardiac cycles recorded four brand Jude patients with mechanical heart valves.
DISCRETE WAVELET TRANSFORM
The wavelet function equation of X (t) to convert the signal shown in Table 1.
Equation 1, X (T) signal to be analyzed. Wavelet function () wavelet function complex conjugate, a parameter expansion (scale), position (displacement) parameter B waves. 2 equations derived from basic wavelet function () is expanding with a scale parameter and is displayed at the transition displacement parameters (Daubechies, 1990; Mallat, 1998; Soltani, 2002; ET Adel al, 2003).
Possible scale and wavelet function equation to calculate the value b 2 is quite laborious and changes in the amount of data is very high. In addition, the use of a compressed wavelet function for calculating the value of the initial and final value of the scale wavelet transform is theoretically infinite. Discrete wavelet transform (included), and b parameters of wavelet function is used for routing and extend the value calculated for the two parties. Thus, the wavelet transform the wavelet transform is calculated for all the values calculated by discretizated expansion and offset values for the two parties.
Parameters A and B, a natural way to discretize through a shift parameter logarithmic discretization () and B-parameter is a parameter associated with the new. B associated with a proportional amount of displacement with a () is designed to be held with both B. Wavelet function is shown in a discretization equation 3 (Addison, 2002).
Equations 3 and m and n are integers, are those that control the amount of compression displacement, respectively, wavelet functions and new parameters. Compression parameter is greater than zero break from a specific set of parameters. And wavelet function normally for a random selection and two parameters. The two forces that make the new scale will be provided logarithmic form. Discretization least two practical choice in terms of political power as the easiest and most effective application discretization. Instead, the problems and values of equality equation 3 is obtained by 4 the new wavelet function.
Add (wavelet series decomposition) series signal known results wavelet decomposition (D (M, N)) states that is obtained as a series of wavelet coefficients. Wavelet coefficients of the wavelet functions signal weighted sum equation for reconstruction is given by 6.
Creating new signal spectrum structure is a theoretical problem in equation (6) band pass filter of the wavelet function. Instead, to put in a basic function of the low frequency components description of the ongoing solution to this problem equation to expand to cover the entire spectrum of the wavelet function to zero to 6 (Valens's, 1999) Is. This is the basic functions of scalar functions. rearrangement of x (t) by using the scaling equations 6 reconstructed signal is given in Equation 7 (Valencia, 1999, Addison, 2002; Burrus ET al., 1998).
Equation 7, m and n are integers, () scalar function () wavelet function () Description (Description) or wavelet coefficients of () approach (approximation) or scale factor. Thus, the original signal equation 7 X (T) mass function defined low frequency changes, the equation x (t) the higher the signal wavelet function by the amount of left-frequency components by the amount on the right side is defined by. Equation 7 signal change in approach and discrete wavelet detail coefficients. These coefficients completely original signal and the signal analysis, can identify and restructuring are used for filtration (Burrus ET al., 1998).
Frequency domain approach and description of the band filter of the wavelet function is used to calculate the coefficients of a low-pass filter function and information on the scale. Based on this information, should be used to count different scale wavelet coefficients, filter bank (filter bank) separation of the low frequency band and examples to identify the signals with extended wavelet function array and scalar functions for price the signal can be found with cuts (Valens 1999, Adele ET al., 2003).
ANALYSIS OF MECHANICAL HEART VALVE SOUNDS WİTH PARAVALVULAR LEAKAGE
Leak repair surgery (KS) and applicable to regular Senate after mechanical heart valve (KO), register Jude patients heart sound signal with the same leakage in patients valves, mechanical heart replacement discrete wavelet patients (N). Discrete wavelet transform discretization levels were five. Thus, in view of the mechanical heart valve audio signals D1, D2, D3, D4, D5 and A5 description is decomposed into subbands. 5000 Hz sampling frequency used in the study 156.25-312.5 Hz Hz frequency and the signal D4 to A5 for 1250-2500 78.125-156.25 Touchstone band 312.5-625 to 625-1250 Hz Hz Hz D5 D1, D2, D3, for the 0-78.125Hz. This results in the separation of raw heart signal can be analyzed separately for different frequency bands mentioned above. The decomposition process is repeated for Daubechies 2, 3, 4, 5, 6, 7, 8, Symlet 2, 3, 4, 5, 6, 7, 8, Coiflet 1, 2, 3, 4, 5 wavelet functions was.
The patient leak repair operation and the signal Daubechies a large patient heartbeat signals of a cardiac cycle of a patient with the sorting until the fifth level wavelet function and a mechanical heart valve, respectively, in Figure 1, 2 and 3 is shown. Nonetheless achieved using a heart cycle of raw heart sound signals of the first line, the fifth level of the game to approximations A5 subband of coefficients, third, fourth, fifth, sixth and using coefficient D5 of the description of the seventh lines , D4, the D3, d2, d1 shows subband.
Of a cardiac cycle detail Add subband signals obtained from approximation coefficients is obtained through the heart chakra of the physical properties is divided into four parts. Heart (systole) and consists of a cycle stage contractions rest (diastole) and. In systole and beginning of the second heart sound first heart sound at the beginning of diastole occurs. This information is divided into sections in the light of the heart cycle; S1 sound shaping, systolic volume first part to leave the second part of which contains S1, S2, the audio portion of the third part, S2 depends on diastolic volume the fourth part of the region, except for the parts.
Shannon heart chakra is the heart of this sound 75ms'lik both sides of the engaging part of the first section at the beginning of a maximum of 20% of energy. The third part of which is composed of the heart sounds. The third part contains the heart and ECG T-wave Shannon cycle energy use. Ie the point wave and 150 ms after more ECG T Shannon energy S2 sound of the center is taken as part of a 50 ms on both sides of the center and are treated as third territories. The second part, the first and the rest of the cardiac cycle end after leaving the systole of the region S1 Sound Four, the S2 sound diastolic area separation as the end of the third part of the third part area.
Thus a cardiac cycle representing the S1 sound (parts1), S2 represents the volume (parts2), S1 representing the area systole except for the sound (partsis) and S2 representing the diastole of excluding audio (partdias) of a heart cycle including sub- divided into four parts .
Each sub-band (ENT), the values of the minimum (min) and a maximum gain of Shannon entropy for each of the four segments (maximum) are calculated as a feature. Paired significant difference between the poor and the resulting 99% confidence limits for the treatment of patients with T-test, the properties of the normal patients as confidence were compared with a unique t-test 99 Whether the characteristics of patients is poor, with significant differences in length. KO by KO (n) and S statistically significant difference between the two results compare with (P <0.01), mean and standard deviation values of the properties are given in Table 1. Table 1 first column feature and wavelet is obtained function, the second column illegal formed patients, mean a patient standard deviation and after normal patients is shown in the third column Leak Repair News features. Audio signal, but the sound of the audio signal phase of systole S1 schedule all the features that have been obtained from 1 partsis. Table 1 from the first line 2 reveals wavelet functions performed by the decomposition of the audio signal Description 5 (D5) in Daubechies partsis coefficient is statistically significant difference between the groups. Are listed in order by notice to the other lines. Figure 4, box plots are given for these attributes.
RESULTS and DISCUSSIONS
This kind of stage heart ventricle pumping blood into the aorta and pulmonary artery forming systole contract are performed cardiac cycle is known as physical events. Mechanical heart valve from the blood hallway leading causes of heart contraction to pass through this opening, connects the heart to the opening of the seam. The same situation can be seen in the atrium and ventricle and aortic valve inertia. Heart failure due to mechanical heart valve leakage in one of the most important disease after mechanical heart valve thrombosis.
According to a different frequency peaks in the spectrum due to the methods used in the literature as faulty mechanical heart valves, mechanical heart valves normal audio signal frequency components to high frequency for both, despite seems to indicate an energy. (The Sava and McDonnell 1996 ;. Zhang ET al., 2009)
These studies features can be found in the same sense that among the other normal systolic region partsis time for patients with frequency domain analysis showed that obtained by the valve mechanical heart sound signals S1 audio signal Difference. Leaks that result after the result of sound mechanical heart valve Q1 and therefore occur where it is easy to understand. Recorded signal strength was obtained in an information leak literature to the spectral density of the test. The leakage could not get the sound signal with both poor physical heart and leaking information to the frequency domain analysis of this isolation was performed by the heart sound signal features. It features specifically for 156.25 D4, are the fourth and fifth degree of detail for the lower limits leakage occurring in mechanical heart valve - 312.5 Hz Hz frequency band and D5 to 78.125-156.25 There appears to be effective.
Table 1 given maxd5, maxd4 and entd4 characteristics associated KS and n mean values are obtained while the average price over mind5 and S and N mind4 of the value of the average values obtained from the project's average less. Figure 4 box drawing features is that the observed values of KO and distribution based on features derived from IO N which is wider than KO and is the NA of the features of the standard deviation obtained from chemical peeling . However, the standard deviation of the features of the big KO and KS KO dataset (n) and does not appear to coincide with the cod. If faulty discrete wavelet transformation of these features are considered to be an important parameter for the assessment of mechanical heart valve sounds. To make sure these preliminary results involved more evidence of the effectiveness need to be educated.
Article Completed