Hemodynamics-driven mathematical model of first and second heart sound generation

We propose a novel, two-degree of freedom mathematical model of mechanical vibrations of the heart that generates heart sounds in CircAdapt, a complete real-time model of the cardiovascular system. Heart sounds during rest, exercise, biventricular (BiVHF), left ventricular (LVHF) and right ventricular heart failure (RVHF) were simulated to examine model functionality in various conditions. Simulated and experimental heart sound components showed both qualitative and quantitative agreements in terms of heart sound morphology, frequency, and timing. Rate of left ventricular pressure (LV dp/dtmax) and first heart sound (S1) amplitude were proportional with exercise level. The relation of the second heart sound (S2) amplitude with exercise level was less significant. BiVHF resulted in amplitude reduction of S1. LVHF resulted in reverse splitting of S2 and an amplitude reduction of only the left-sided heart sound components, whereas RVHF resulted in a prolonged splitting of S2 and only a mild amplitude reduction of the right-sided heart sound components. In conclusion, our hemodynamics-driven mathematical model provides fast and realistic simulations of heart sounds under various conditions and may be helpful to find new indicators for diagnosis and prognosis of cardiac diseases. New & noteworthy To the best of our knowledge, this is the first hemodynamic-based heart sound generation model embedded in a complete real-time computational model of the cardiovascular system. Simulated heart sounds are similar to experimental and clinical measurements, both quantitatively and qualitatively. Our model can be used to investigate the relationships between heart sound acoustic features and hemodynamic factors/anatomical parameters.

End-to-end heart sound segmentation using deep convolutional recurrent network

Heart sound segmentation (HSS) aims to detect the four stages (first sound, systole, second heart sound and diastole) from a heart cycle in a phonocardiogram (PCG), which is an essential step in automatic auscultation analysis. Traditional HSS methods need to manually extract the features before dealing with HSS tasks. These artificial features highly rely on extraction algorithms, which often result in poor performance due to the different operating environments. In addition, the high-dimension and frequency characteristics of audio also challenge the traditional methods in effectively addressing HSS tasks. This paper presents a novel end-to-end method based on convolutional long short-term memory (CLSTM), which directly uses audio recording as input to address HSS tasks. Particularly, the convolutional layers are designed to extract the meaningful features and perform the downsampling, and the LSTM layers are developed to conduct the sequence recognition. Both components collectively improve the robustness and adaptability in processing the HSS tasks. Furthermore, the proposed CLSTM algorithm is easily extended to other complex heart sound annotation tasks, as it does not need to extract the characteristics of corresponding tasks in advance. In addition, the proposed algorithm can also be regarded as a powerful feature extraction tool, which can be integrated into the existing models for HSS. Experimental results on real-world PCG datasets, through comparisons to peer competitors, demonstrate the outstanding performance of the proposed algorithm.

Loud P2 on Cardiac Auscultation: A Useful Clinical Clue to Fluid Overload

Patients with renal disease are at risk of fluid overload which escalates as the disease progresses. In the present study, we evaluated the increase in the intensity of the second heart sound generated by its pulmonary component (P2) and its correlation with fluid overload in such patients. To confirm its potentials and avoid interference with patients with cardiac disease; we included only those who lacked echocardiographic evidence of (a) ASD or VSD, (b) primary cardiac defects associated with high P2 viz pulmonary aneurysm, mitral stenosis and myocardial disease, (c) primary cardiac defects associated with soft P2 viz pulmonary stenosis, pulmonary atresia and tetralogy of Fallot, (d) primary cardiac defects associated with low A2 viz mitral regurgitation, aortic regurgitation, low diastolic arterial pressure, severe immobile aortic valve disease. To assess the extent of fluid overload; the clinical examination was complemented with radiological imaging as well as the echocardiographic measurement of systolic pulmonary arterial pressure. There was a significant correlation between P2 intensity and fluid changes. In conclusion; load P2 is a useful clinical clue to fluid overload and decline in its intensity correlates with the extent of fluid removal.

Additional Heart Sounds—Part 1 (Third and Fourth Heart Sounds)

S3 is a low-pitched sound (25–50Hz) which is heard in early diastole, following the second heart sound. The following synonyms are used for it: ventricular gallop, early diastolic gallop, protodiastolic gallop, and ventricular early filling sound. The term “gallop” was first used in 1847 by Jean Baptiste Bouillaud to describe the cadence of the three heart sounds occurring in rapid succession. The best description of a third heart sound was provided by Pierre Carl Potain who described an added sound which, in addition to the two normal sounds, is heard like a bruit completing the triple rhythm of the heart (bruit de gallop). The following synonyms are used for the fourth heart sound (S4): atrial gallop and presystolic gallop. S4 is a low-pitched sound (20–30 Hz) heard in presystole, i.e., shortly before the first heart sound. This produces a rhythm classically compared with the cadence of the word “Tennessee.” One can also use the phrase “A-stiff-wall” to help with the cadence (a S4, stiff S1, wall S2) of the S4 sound.

A Pregnant Lady with Thyrotoxic Cardiomyopathy and Pulmonary Hypertension

Thyrotoxic cardiomyopathy is potentially life threatening complications of thyrotoxicosis during pregnancy due to its harmful effects both on mother and fetus. We present a case of 32-year-old pregnant lady presented with non-productive cough, palpitation, restlessness, sweating and weakness after minimum exertion with a small swelling on the right side of her neck for three months. There was tachycardia with normal blood pressure, first and second heart sound were soft with pansystolic murmur on mitral and tricuspid area. After all laboratory investigations, she was diagnosed as dilated cardiomyopathy with moderate to severe pulmonary hypertension with toxic multi nodular goiter with 13 weeks of pregnancy.The thyrotoxic cardiomyopathy during pregnancy is rare due to difficulties in diagnosis. However, physicians should be aware of the risk posed by thyrotoxic cardiomyopathy during pregnancy. KYAMC Journal Vol. 11, No.-1, April 2020, Page 54-56

Electronic Stethoscope Design

Nowadays, despite the developing technology lots of patients lost their lives because of wrong and late diagnosis. With early diagnosis, most diseases and negative effects of the diseases for the patient can be prevented. Early diagnosis can also prevent cardiological diseases. Although auscultation of the chest with a stethoscope is an effective and basic method, a stethoscope isn't enough for the diagnosis of some diseases. One example of these diseases is heart valve malfunctions when the valves do not work as desired heart murmurs occur. The main goal of this project is to develop an electronic stethoscope and observing obtained signals as a graphic. The main difficulty while auscultation of chest with a stethoscope is, this procedure needs lots of experience and also even tough physician have enough experience, it's very hard to diagnose grade 1 and 2 heart murmurs. Furthermore, while auscultation tachycardia patients, generally it's very hard to decide where the first heart (S1) sound and second heart sound (S2) begins. In this project, it is planned to demonstrate heart sounds as a graphic. This method provides physicians to diagnose all kinds of chest sounds easily even the sounds which they cannot diagnose or recognize with their ears by stethoscope. Moreover, as the chest sounds are obtained as digital data, these data can be sent as desired. When a physician needs to get someone else's idea, these recordings can be sent to another professional.