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ABSTRACT: The second heart sound, S2, is generally believed to be comprised of aortic (A2) and pulmonary (P2) components. Previously, the normalized splitting interval (NSI) between the A2 and P2 components has been shown to be proportional to the pulmonary artery pressure (PAP). A set of fully automated algorithms based on adaptive modeling of A2/P2 components using chirplets were developed to provide real-time estimates of PAP. The method was tested on 16 pigs which were administered drugs to induce pulmonary hypertension. Simultaneous reference pressure measurements were obtained with a pulmonary artery catheter (PAC). Estimation of PAP in pigs using the new techniques resulted in a correlation coefficient (r) of 0.84 and standard error (SEE) of 9.2 mm Hg. This is in line with echocardiography studies, which have a performance ranging from r=0.69-0.91 and SEE from 5 to 12 mm Hg when compared to PAC measurements. It is also consistent with previous results based on a manual estimation of PAP derived through image processing methods. Based on these findings, this method has the potential to offer continuous noninvasive monitoring of PAP.
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE; 10/2004
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[show abstract]
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ABSTRACT: The second heart sound, S2, is generally believed to be comprised of aortic (A2) and pulmonary (P2) components. Previously, the normalized splitting interval (NSI) between the A2 and P2 components has been shown to be proportional to the pulmonary artery pressure (PAP). A set of fully automated algorithms based on adaptive modeling of A2/P2 components using chirplets were developed to provide real-time estimates of PAP. The method was tested on 16 pigs which were administered drugs to induce pulmonary hypertension. Simultaneous reference pressure measurements were obtained with a pulmonary artery catheter (PAC). Estimation of PAP in pigs using the new techniques resulted in a correlation coefficient (r) of 0.84 and standard error (SEE) of 9.2 mm Hg. This is in line with echocardiography studies, which have a performance ranging from r=0.69-0.91 and SEE from 5 to 12 mm Hg when compared to PAC measurements. It is also consistent with previous results based on a manual estimation of PAP derived through image processing methods. Based on these findings, this method has the potential to offer continuous noninvasive monitoring of PAP.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2004; 2:921-4.
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ABSTRACT: To develop and validate a new non-invasive method for the estimation of pulmonary arterial pressure (PAP) based on advanced signal processing of the second heart sound.
Prospective comparative study.
Referral cardiology centre.
This method was first tested in 16 pigs with experimentally induced pulmonary hypertension and then in 23 patients undergoing pulmonary artery catheterisation.
The heart sounds were recorded at the surface of the thorax using a microphone connected to a personal computer. The splitting time interval between the aortic and the pulmonary components of the second heart sound was measured using a computer assisted spectral dechirping method and was normalised for heart rate.
The systolic PAP varied between 14-73 mm Hg in pigs and between 20-70 mm Hg in patients. The normalised splitting interval was measurable in 97% of the recordings made in pigs and 91% of the recordings made in patients. There was a strong relation between the normalised splitting interval and the systolic PAP (pigs: r = 0.94, standard error of the estimate (SEE) = 5.3 mm Hg; patients: r = 0.84, SEE = 7.8 mm Hg) or the mean pulmonary pressure (pigs: r = 0.94, SEE = 4.1 mm Hg; patients: r = 0.85, SEE = 5.8 mm Hg).
This study shows that this new non-invasive method based on advanced signal processing of the second heart sound provides an accurate estimation of the PAP.
Heart (British Cardiac Society) 08/2002; 88(1):76-80. · 4.22 Impact Factor
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ABSTRACT: The objective of this paper is to adapt and validate a nonlinear transient chirp signal modeling approach for the analysis and synthesis of overlapping aortic (A2) and pulmonary (P2) components of the second heart sound (S2). The approach is based on the time-frequency representation of multicomponent signals for estimating and reconstructing the instantaneous phase and amplitude functions of each component. To evaluate the accuracy of the approach, a simulated S2 with A2 and P2 components having different overlapping intervals (5-30 ms) was synthesized. The simulation results show that the technique is very effective for extracting the two components, even in the presence of noise (-15 dB). The normalized root-mean-squared error between the original A2 and P2 components and their reconstructed versions varied between 1% and 6%, proportionally to the duration of the overlapping interval, and it increased by less than 2% in the presence of noise. The validated technique was then applied to S2 components recorded in pigs under normal or high pulmonary artery pressures. The results show that this approach can successfully isolate and extract overlapping A2 and P2 components from successive S2 recordings obtained from different heartbeats of the same animal as well from different animals.
IEEE Transactions on Biomedical Engineering 04/2001; 48(3):277-83. · 2.28 Impact Factor
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ABSTRACT: This paper describes a new approach based on the time-frequency representation of transient nonlinear chirp signals for modeling the aortic (A2) and the pulmonary (P2) components of the second heart sound (S2). It is demonstrated that each component is a narrow-band signal with decreasing instantaneous frequency defined by its instantaneous amplitude and its instantaneous phase. Each component is also a polynomial phase signal, the instantaneous phase of which can be accurately represented by a polynomial having an order of thirty. A dechirping approach is used to obtain the instantaneous amplitude of each component while reducing the effect of the background noise. The analysis-synthesis procedure is applied to 32 isolated A2 and 32 isolated P2 components recorded in four pigs with pulmonary hypertension. The mean +/- standard deviation of the normalized root-mean-squared error (NRMSE) and the correlation coefficient (rho) between the original and the synthesized signal components were: NRMSE = 2.1 +/- 0.3% and rho = 0.97 +/- 0.02 for A2 and NRMSE = 2.52 +/- 0.5% and rho = 0.96 +/- 0.02 for P2. These results confirm that each component can be modeled as mono-component nonlinear chirp signals of short duration with energy distributions concentrated along its decreasing instantaneous frequency.
IEEE Transactions on Biomedical Engineering 11/2000; 47(10):1328-35. · 2.28 Impact Factor
