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.

Valvular heart disease

Rheumatic valve disease remains prevalent in developing countries, but over the last 50 years there has been a decline in the incidence of rheumatic valve disease and an increase in the prevalence of degenerative valve pathology in northern Europe and North America. In all forms of valve disease, the most appropriate initial diagnostic investigation is almost always the echocardiogram. The most common cause is rheumatic valve disease. Other causes include mitral annular calcification, congenital mitral stenosis, infective endocarditis (very rarely), and systemic lupus erythematosus (Liebman–Sachs endocarditis). The important consequences of mitral stenosis are its effect on left atrial pressure, size, and the pulmonary vasculature; it commonly causes atrial fibrillation. Presenting symptoms are typically exertional fatigue and breathlessness; systemic embolism can occur. Characteristic physical signs are irregular pulse, tapping apex beat, loud first heart sound, opening snap, and an apical low-pitched rumbling mid-diastolic murmur.

Calculation the precision of the conversion of bio-signals (heart sounds) in analog to digital and digital to analog conversion processes in ATmega 8 microcontroller processors using computer simulation

The research aims to calculate the precision transfer from the analogue to digital convertor (ADC) and the digital to analogue convertor (DAC) of the ATmega microcontroller series that are widely used in various circuits and their application of weak signals such as boi-signals, especially heart sounds signals.We chose the ATmega8 microcontroller and performed the measurements and results on the first heart sound (S1) after enforcement the simulations of an electronic stethoscope using the famous program proteus8 for electronic systems. We performed the analogue to digital conversion (ADC) for 20 samples of the signal and then we performed the opposite process DAC using 2R-R resistor network with 10 inputs.The results obtained showed a near perfect match between the signals before and after the conversion. Which suits this type of application.

Blind Separation of Heart Sounds

This paper presents a theoretical foundation for the newly developed methodology that enables the prediction of blood pressures based on the heart sounds measured directly on the chest of a patient. The key to this methodology is the separation of heart sounds into first heart sound and second heart sound, from which components attributable to four heart valves, i.e.: mitral; tricuspid; aortic; and pulmonary valve-closure sounds are separated. Since human physiology and anatomy can vary among people and are unknown a priori, such separation is called blind source separation. Moreover, the sources locations, their surroundings and boundary conditions are unspecified. Consequently, it is not possible to obtain an exact separation of signals. To circumvent this difficulty, we extend the point source separation method in this paper to an inhomogeneous fluid medium, and further combine it with iteration schemes to search for approximate source locations and signal propagation speed. Once these are accomplished, the signals emitted from individual sources are separated by deconvoluting mixed signals with respect to the identified sources. Both numerical simulation example and experiment have demonstrated that this approach can provide satisfactory source separation results.

Nonlinear Time Domain Relation between Respiratory Phase and Timing of the First Heart Sound

The previous studies on respiratory physiology have indicated that inspiration and expiration have opposite effects on heart hemodynamics. The basic reason why these opposite hemodynamic changes cause regular timing variations in heart sounds is the heart sound generation mechanism that the acoustic vibration is triggered by heart hemodynamics. It is observed that the timing of the first heart sound has nonlinear relation with respiratory phase; that is, the timing delay with respect to the R-wave increases with inspiration and oppositely decreases with expiration. This paper models the nonlinear relation by a Hammerstein-Wiener model where the respiratory phase is the input and the timing is the output. The parameter estimation for the model is presented. The model is tested by the data collected from 12 healthy subjects in terms of mean square error and model fitness. The results show that the model can approximate the nonlinear relation very well. The average square error and the average fitness for all the subjects are about 0.01 and 0.94, respectively. The timing of the first heart sound related to respiratory phase can be accurately predicted by the model. The model has potential applications in fast and easy monitoring of respiration and heart hemodynamics induced by respiration.