The Role of Heart Sounds Recording and Analysis in the Dyspneic Ed Patient
نویسنده
چکیده
Extra diastolic heart sounds are produced as a result of increased stiffness and decreased compliance of the left ventricle. The third heart sound (S3) occurs 0.12 to 0.16 seconds after the second heart sound in early diastole (Figure 1). Of the many proposed theories, the most likely explanation is that excessive rapid fi lling of a stiff ventricle is suddenly halted, causing vibrations that are audible as the third heart sound. The fourth heart sound (S4) occurs after P wave onset and before the fi rst heart sound in the cardiac cycle. It is produced in late diastole as a result of atrial contraction causing vibrations of the left ventricular muscle, mitral valve apparatus, and left ventricular blood mass. Atrial and ventricular “gallops” have been described in the literature dating back to the late 1800’s. The ventricular gallop is recognized as a third heart sound. The atrial gallop is synonymous with a fourth heart sound. Auscultation of the S3 and S4 Both an S3 and S4 are auscultated in similar fashion. Harvey has suggested the “inching” technique as a way to distinguish the often times pathologic S3 and S4 from the physiologic S1 and S2. In both situations it is best to examine the patient in the left lateral position using the bell of the stethoscope. Starting at the aortic area (where the S2 is the loudest) the examiner “inches” down to the cardiac apex, using the S2 as a reference point. If one encounters an extra sound in diastole, just after the S2, this is an S3 or diastolic gallop. The S3 is generally absent at the base, so that as the examiner moves toward the apex the S3 is encountered. The opposite maneuver results in detection of an S4. In this instance the examiner inches from the apex upward Figure 1.
منابع مشابه
Automatic classification of normal and abnormal cardiac sounds by combining features based on wavelet transform and capstral coefficients extracted from PCG signals (Research Article)
Cardiac sounds are produced by the mechanical activities of the heart and provide useful information about the function of the heart valves. Due to the transient and unstable nature of the heart's sound and the limitation of the human hearing system, it is difficult to categorize heart sound signals based on what is heard from a stethoscope. Therefore, providing an automated algorithm for prima...
متن کاملPSEUDOANEURYSM OF RIGHT VENTRICLE DUE TO LOCALIZED TUBERCULOSIS OF MYOCARDIUM: A CASE REPORT
A 5-year-old girl was admitted to the hospital with chest pain, fever and dyspnea. Physical examination showed normal heart sounds, diminished pulmonary sounds in the left hemithorax and a normal ECG. On chest X-ray the heart was slightly enlarged with moderate left pleural effusion. CT scan revealed pleural effusion and a hypodense mass at the apex of the heart. A cystic mass was detected...
متن کاملDetermining the effective features in classification of heart sounds using trained intelligent network and genetic algorithm
Heart diseases are among the most important causes of mortality in the world, especially in industrial countries. Using heart sounds and the features extracted from them are among the non-aggressive diagnosis and prognosis methods for heart diseases. In this study, the time-scale, Cepstral, frequency, temporal and turbulence features are saved and extracted from the heart sounds, and then they ...
متن کاملSelecting effective features from Phonocardiography by Genetic Algorithm based on Pearson`s Coefficients Correlation
The heart is one of the most important organs in the body, which is responsible for pumping blood into the valvular systems. Beside, heart valve disorders are one of the leading causes of death in the world. These disorders are complications in the heart valves that cause the valves to deform or damage, and as a result, the sounds caused by their opening and closing compared to a healthy heart....
متن کاملA Hybrid Model of Heart Anomalies Detection by Processing Heart Sounds
Introduction: Different factors are effective in detecting heart abnormalities. The greater the number of these factors, the greater the uncertainty in the detection of heart abnormalities. In the uncertainty condition in response of prediction model, the fuzzy systems are one of the most effective methods for generating an acceptable response. Method: In this applied study, 3240 records rela...
متن کامل