- Third and Fourth Heart Sounds and Myocardial Fibrosis in Hypertrophic Cardiomyopathy. [Journal Article]
- CJCirc J 2018 Jan 25; 82(2):509-516
- CONCLUSIONS: Myocardial fibrosis, as assessed by LGE, was associated with S3 but not with S4 in patients with HCM. These results may contribute to the risk stratification of patients with HCM.
- Cardiac Auscultation for Noncardiologists: Application in Cardiac Rehabilitation Programs: PART I: PATIENTS AFTER ACUTE CORONARY SYNDROMES AND HEART FAILURE. [Journal Article]
- JCJ Cardiopulm Rehabil Prev 2017; 37(5):315-321
- During outpatient cardiac rehabilitation after an acute coronary syndrome or after an episode of congestive heart failure, a careful, periodic evaluation of patients' clinical and hemodynamic status ...
During outpatient cardiac rehabilitation after an acute coronary syndrome or after an episode of congestive heart failure, a careful, periodic evaluation of patients' clinical and hemodynamic status is essential. Simple and traditional cardiac auscultation could play a role in providing useful prognostic information.Reduced intensity of the first heart sound (S1), especially when associated with prolonged apical impulse and the appearance of added sounds, may help identify left ventricular (LV) dysfunction or conduction disturbances, sometimes associated with transient myocardial ischemia. If both S1 and second heart sound (S2) are reduced in intensity, a pericardial effusion may be suspected, whereas an increased intensity of S2 may indicate increased pulmonary artery pressure. The persistence of a protodiastolic sound (S3) after an acute coronary syndrome is an indicator of severe LV dysfunction and a poor prognosis. In patients with congestive heart failure, the association of an S3 and elevated heart rate may indicate impending decompensation. A presystolic sound (S4) is often associated with S3 in patients with LV failure, although it could also be present in hypertensive patients and in patients with an LV aneurysm. Careful evaluation of apical systolic murmurs could help identifying possible LV dysfunction or mitral valve pathology, and differentiate them from a ruptured papillary muscle or ventricular septal rupture. Friction rubs after an acute myocardial infarction, due to reactive pericarditis or Dressler syndrome, are often associated with a complicated clinical course.During cardiac rehabilitation, periodic cardiac auscultation may provide useful information about the clinical-hemodynamic status of patients and allow timely detection of signs, heralding possible complications in an efficient and low-cost manner.
- Variation in effectiveness of a cardiac auscultation training class with a cardiology patient simulator among heart sounds and murmurs. [Journal Article]
- JCJ Cardiol 2017; 70(2):192-198
- CONCLUSIONS: Medical students may be less likely to correctly identify S2/S3/S4 as compared with heart murmurs in a situation close to clinical setting even immediately after training. We may have to consider such a characteristic of students when we provide them with cardiac auscultation training.
- Assessment of cardiovascular disease in the donkey: clinical, echocardiographic and pathological observations. [Journal Article]
- VRVet Rec 2016 Oct 15; 179(15):384
- The Donkey Sanctuary (DS) owns 3500-4000 donkeys, estimated to be about 35 per cent of the UK population. Although postmortem surveys suggest a high prevalence of cardiovascular disease in donkeys, t...
The Donkey Sanctuary (DS) owns 3500-4000 donkeys, estimated to be about 35 per cent of the UK population. Although postmortem surveys suggest a high prevalence of cardiovascular disease in donkeys, there is sparse clinical information about cardiovascular examination findings and echocardiographic findings in health and disease. In this cross-sectional study, auscultation findings were recorded, and in a subset of donkeys, echocardiography was used to screen for structural and functional cardiac disease. 202 donkeys were examined; 117 geldings and 85 females. Heart sounds S1 and S2 were detected in all donkeys, but none had audible S3. S4 was detected in nine (4.5 per cent; significantly older than those without S4; P<0.001). A heart murmur was detected in four donkeys. Echocardiography identified these to be due to a ventricular septal defect in one, and aortic regurgitation in three. An additional 43 donkeys had echocardiography. A further 10 donkeys were identified to have aortic insufficiency, but no other valvular regurgitation. 76/202 donkeys subsequently underwent postmortem examination. Three showed degenerative aortic valve changes. One donkey had nodular lesions in the intima of proximal aorta and sinus of Valsalva. Histopathology showed multifocal chronic nodular eosinophilic arteritis, consistent with verminous arteritis. The DS pathology database identified other similar cases.
- Multistage decision-based heart sound delineation method for automated analysis of heart sounds and murmurs. [Journal Article]
- HTHealthc Technol Lett 2015; 2(6):156-63
- A robust multistage decision-based heart sound delineation (MDHSD) method is presented for automatically determining the boundaries and peaks of heart sounds (S1, S2, S3, and S4), systolic, and diast...
A robust multistage decision-based heart sound delineation (MDHSD) method is presented for automatically determining the boundaries and peaks of heart sounds (S1, S2, S3, and S4), systolic, and diastolic murmurs (early, mid, and late) and high-pitched sounds (HPSs) of the phonocardiogram (PCG) signal. The proposed MDHSD method consists of the Gaussian kernels based signal decomposition (GSDs) and multistage decision-based delineation (MDBD). The GSD algorithm first removes the low-frequency (LF) artefacts and then decomposes the filtered signal into two subsignals: the LF sound part (S1, S2, S3, and S4) and the high-frequency sound part (murmurs and HPSs). The MDBD algorithm consists of absolute envelope extraction, adaptive thresholding, and fiducial point determination. The accuracy and robustness of the proposed method is evaluated using various types of normal and pathological PCG signals. Results show that the method achieves an average sensitivity of 98.22%, positive predictivity of 97.46%, and overall accuracy of 95.78%. The method yields maximum average delineation errors of 4.52 and 4.14 ms for determining the start-point and end-point of sounds. The proposed multistage delineation algorithm is capable of improving the delineation accuracy under time-varying amplitudes of heart sounds and various types of murmurs. The proposed method has significant potential applications in heart sounds and murmurs classification systems.
- Utility of the physical examination in detecting pulmonary hypertension. A mixed methods study. [Journal Article]
- PlosPLoS One 2014; 9(10):e108499
- CONCLUSIONS: The presence of a loud P2 or audible right-sided 4th heart sound are associated with PH. However the physical examination is unreliable for determining the presence of PH.
- An automated tool for localization of heart sound components S1, S2, S3 and S4 in pulmonary sounds using Hilbert transform and Heron's formula. [Journal Article]
- SSpringerplus 2013; 2:512
- The primary problem with lung sound (LS) analysis is the interference of heart sound (HS) which tends to mask important LS features. The effect of heart sound is more at medium and high flow rate tha...
The primary problem with lung sound (LS) analysis is the interference of heart sound (HS) which tends to mask important LS features. The effect of heart sound is more at medium and high flow rate than that of low flow rate. Moreover, pathological HS obscures LS in a higher degree than normal HS. To get over this problem, several HS reduction techniques have been developed. An important preprocessing step in HS reduction is localization of HS components. In this paper, a new HS localization algorithm is proposed which is based on Hilbert transform (HT) and Heron's formula. In the proposed method, the HS included segment is differentiated from the HS excluded segment by comparing their area with an adaptive threshold. The area of a HS component is calculated from the Hilbert envelope using Heron's triangular formula. The method is tested on real recorded and simulated HS corrupted LS signals. All the experiments are conducted under low, medium and high breathing flow rates. The proposed method shows a better performance than the comparative Singular Spectrum Analysis (SSA) based method in terms of accuracy (ACC), detection error rate (DER), false negative rate (FNR), and execution time (ET).
- Reducing cardiovascular mortality in chronic kidney disease: something borrowed, something new. [Case Reports]
- JCIJ Clin Invest 2013 Feb 1; 123(2):542-3
- CLINICAL VIGNETTE: A 48-year-old man with chronic kidney disease stage five due to type II diabetes mellitus and hypertension was referred for hemodialysis initiation. His physical exam showed a bloo...
CLINICAL VIGNETTE: A 48-year-old man with chronic kidney disease stage five due to type II diabetes mellitus and hypertension was referred for hemodialysis initiation. His physical exam showed a blood pressure of 150/80, normal fundi, a positive fourth heart sound (S4), and trace pedal edema. Moderate aortic calcification was present on prior chest X-ray. The ECG showed left ventricle hypertrophy by voltage and slight prolongation of the QT interval. Medications included chlorthalidone, amlodipine, carvedilol, cholecalciferol, erythropoietin, and a phosphate binder. What additional therapy should be initiated to reduce vascular calcifications and cardiovascular mortality?
- Analysis of the pathological severity degree of aortic stenosis (AS) and mitral stenosis (MS) using the discrete wavelet transform (DWT). [Review]
- JMJ Med Eng Technol 2013; 37(1):61-74
- The heart is the principal organ that circulates blood. In normal conditions it produces four sounds for each cardiac cycle. However, most often only two sounds appear essential: S1 and S2. Two other...
The heart is the principal organ that circulates blood. In normal conditions it produces four sounds for each cardiac cycle. However, most often only two sounds appear essential: S1 and S2. Two other sounds: S3 and S4, with lower amplitude than S1 or S2, appear occasionally in the cardiac cycle by the effect of disease or age. The presence of abnormal sounds in one cardiac cycle provide valuable information on various diseases. The aortic stenosis (AS), as being a valvular pathology, is characterized by a systolic murmur due to a narrowing of the aortic valve. The mitral stenosis (MS) is characterized by a diastolic murmur due to a reduction in the mitral valve. Early screening of these diseases is necessary; it's done by a simple technique known as: phonocardiography. Analysis of phonocardiograms signals using signal processing techniques can provide for clinicians useful information considered as a platform for significant decisions in their medical diagnosis. In this work two types of diseases were studied: aortic stenosis (AS) and mitral stenosis (MS). Each one presents six different cases. The application of the discrete wavelet transform (DWT) to analyse pathological severity of the (AS and MS was presented. Then, the calculation of various parameters was performed for each patient. This study examines the possibility of using the DWT in the analysis of pathological severity of AS and MS.
New Search Next
- A low-cost, portable, high-throughput wireless sensor system for phonocardiography applications. [Journal Article]
- SSensors (Basel) 2012; 12(8):10851-70
- This paper presents the design and testing of a wireless sensor system developed using a Microchip PICDEM developer kit to acquire and monitor human heart sounds for phonocardiography applications. T...
This paper presents the design and testing of a wireless sensor system developed using a Microchip PICDEM developer kit to acquire and monitor human heart sounds for phonocardiography applications. This system can serve as a cost-effective option to the recent developments in wireless phonocardiography sensors that have primarily focused on Bluetooth technology. This wireless sensor system has been designed and developed in-house using off-the-shelf components and open source software for remote and mobile applications. The small form factor (3.75 cm × 5 cm × 1 cm), high throughput (6,000 Hz data streaming rate), and low cost ($13 per unit for a 1,000 unit batch) of this wireless sensor system make it particularly attractive for phonocardiography and other sensing applications. The experimental results of sensor signal analysis using several signal characterization techniques suggest that this wireless sensor system can capture both fundamental heart sounds (S1 and S2), and is also capable of capturing abnormal heart sounds (S3 and S4) and heart murmurs without aliasing. The results of a denoising application using Wavelet Transform show that the undesirable noises of sensor signals in the surrounding environment can be reduced dramatically. The exercising experiment results also show that this proposed wireless PCG system can capture heart sounds over different heart conditions simulated by varying heart rates of six subjects over a range of 60-180 Hz through exercise testing.