Analyzing approaches to mathematic modeling of heart sounds

The article introduces the findings of the analysis of the existing approaches to the development of mathematical models of acoustic heart phenomena. The analysis of mathematical methods that can be used to model heart sounds has been performed with the use of reference signals from the 3M Open Library (Littmann Library) and a set of signals obtained by the authors during their previous scientific efforts. The analysis findings have allowed revealing the approaches and methods that are most suitable for developing the mathematical models of human phonocardiograms (normal and pathological) for further research efforts meant to develop methods to single out heart beats against the high level of interference and creating intervalograms to characterize the heart rate at the current moments of time. In addition to the generation of model phonocardiograms, the article reviews the methods to analyze model and real-life phonocardiograms with the assessment of an input from random and deterministic components.

A hybrid method for fundamental heart sound segmentation using group-sparsity denoising and variational mode decomposition

Segmentation of fundamental heart sounds–S1 and S2 is important for automated monitoring of cardiac activity including diagnosis of the heart diseases. This pa-per proposes a novel hybrid method for S1 and S2 heart sound segmentation using group sparsity denoising and variation mode decomposition (VMD) technique. In the proposed method, the measured phonocardiogram (PCG) signals are denoised using group sparsity algorithm by exploiting the group sparse (GS) property of PCG signals. The denoised GS-PCG signals are then decomposed into subsequent modes with specific spectral characteristics using VMD algorithm. The appropriate mode for further processing is selected based on mode central frequencies and mode energy. It is then followed by the extraction of Hilbert envelope (HEnv) and a thresholding on the selected mode to segment S1 and S2 heart sounds. The performance advantage of the proposed method is verified using PCG signals from benchmark databases namely eGeneralMedical, Littmann, Washington, and Michigan. The proposed hybrid algorithm has achieved a sensitivity of 100%, positive predictivity of 98%, accuracy of 98% and detection error rate of 1.5%. The promising results obtained suggest that proposed approach can be considered for automated heart sound segmentation.

A new approach for blood pressure estimation based on phonocardiogram

Continuous and non-invasive measurement of blood pressure (BP) is of great importance particularly for patients in critical state. To achieve continuous and cuffless BP monitoring, pulse transit time (PTT) has been reported as a potential parameter. Nevertheless, this approach remains very sensitive, cumbersome and disagreeable in ambulatory measurement. This paper proposes a new approach to estimate blood pressure through PCG signal by exploring the correlation between PTT and diastolic duration (S21). In this purpose, an artificial neural network was developed using as input data: (systolic duration, diastolic duration, heart rate, sex, height and weight). According to the NN decision, the mean blood pressure was measured and consequently the systolic and the diastolic pressures were estimated. The proposed method is evaluated on 37 subjects. The obtained results are satisfactory, where, the error in the estimation of the systolic and the diastolic pressures compared to the commercial blood pressure device was in the order of 6 .48 ± 4.48 mmHg and 3 .91 ± 2.58 mmHg, respectively, which are very close to the AAMI standard, 5 ± 8 mmHg. This shows the feasibility of estimating of blood pressure using PCG.

Automatic heart activity diagnosis based on Gram polynomials and probabilistic neural networks

The paper proposes a new approach to heart activity diagnosis based on Gram polynomials and probabilistic neural networks (PNN). Heart disease recognition is based on the analysis of phonocardiogram (PCG) digital sequences. The PNN provides a powerful tool for proper classification of the input data set. The novelty of the proposed approach lies in a powerful feature extraction based on Gram polynomials and the Fourier transform. The proposed system presents good performance obtaining overall sensitivity of 93%, specificity of 91% and accuracy of 94%, using a public database of over 3000 heart beat sound recordings, classified as normal and abnormal heart sounds. Thus, it can be concluded that Gram polynomials and PNN prove to be a very efficient technique using the PCG signal for characterizing heart diseases.

A relative value method for measuring and evaluating neonatal cardiac reserve.

Objective. To devise some indicators for measuring and evaluating the neonatal cardiac reserve by using phonocardiogram test (PCGT). Methods. Two hundred and thirty one (231) full term and one hundred and fifty four (154) preterm infants participated in this study. The amplitude ratio of the first heart sound to the second heart sound (S1/S2), the ratio of diastolic to systolic duration (D/S) and the cardiac contractility change trend after stimulation (CCCTS) of the neonates were measured, calculated and analyzed. Results. The S1/S2, D/S and CCCTS of full preterm infants were higher than that of preterm infants. The differences of D/S and CCCTS between them were significant (P<0.05). According to the full term neonatal cardiac reserve data, a normal reference range of full term neonatal cardiac reserve was primarily known. Conclusions. The indicators S1/S2, D/S and CCCTS may be beneficial for evaluating the neonatal cardiac reserve. We can screen out neonates with reduced cardiac reserve by using the phonocardiogram test.

A Novel Method for Extraction of Heart Sounds Envelope Based on Interpolation of Local Peak and Valley Points / 航天医学与医学工程

Objective To extract envelope of heart sounds exactly,for the purpose of the further analysis of its characteristics.Methods The way that envelope extraction of heart sounds based on key-points was given.The points of local peak and valley were calculated firstly,and then heart sound envelope was gotten by the interpolation of these points.Results Compared with the envelope extracted by Hilbert-transform and mathematical morphology,respectively,the outline of heart sounds was extracted more accurately,and its time-domain characters were acquired by this method.Conclusion The envelope of heart sound is extracted correctly by this method,which is useful for the further analysis.

Clinical study on evaluating the function of cardiac reserve in hypertensive patients with noninvasive techniques / 重庆医科大学学报

Objective:To explore whether phonocardiogram exercise test(PCGET) or doppler echocardiography can sensitively and specifically detect the changes of cardiac reserve in patients with hypertension and whether there is a relationship between the two methods.Methods:The trail was performed with eighty volunteers, including twenty healthy persons as control group,and sixty hypertensive patients, which were divided into three subgroups:hypertension A, HA(patients without left ventricular hypertrophy,LVH and enlarged left ventricle);hypertension B, HB(patients with only LVH) and hypertension C,HC(patients with both LVH and enlarged left ventricle).The cardiac contractility reserve index(CCRI) was measured by PCGET, while the value of LV end-systolic and end-diastolic long and short axis dimensions, wall thickness and synchronous blood pressure were measured by the technique of simultaneous screen display of electrocardiography and synchronously monitoring blood pressure.According to the parameters measured by the latter technique, the values of maximum elasticity(Emax), the average maximum myocardial elasticity stiffness(maxEav) and ejection fraction(EF)were calculated by computer programmed process.Results:(1)Compared with control group,there was a statistically significant difference between the hypertension groups except HA group,and also an obvious difference between HB and HC about the indexes of Emax, maxEav and EF(P

Design of virtual instrument for measuring phonocardiogram based on LabVIEW / 医疗卫生装备

Phonocardiogram contains a lot of information on the physiological and pathological cardiac function, so it can improve the diagnosis and treatment of cardiovascular disease to effectively diagnose cardiac sounds. This paper presents the design of a computer-based measurement and real-time analysis system of heart sounds. Applying computers to the analysis and auxiliary diagnosis of cardiac sounds, the system is real-time and intelligent.