APPLICATION OF DIGITAL PROCESSING OF HEART SOUNDS TO HEART VALVE MODELLING

1982 ◽  
pp. 639-642
Author(s):  
D. Nandagopal ◽  
J. Mazumdar ◽  
R.E. Bogner ◽  
G. Karolyi
Keyword(s):  
Heart Valve ◽  
Digital Processing ◽  
Heart Sounds

scholarly journals Application of Digital Processing of Heart Sounds To Heart Valve Modelling

1982 ◽  
Vol 15 (1) ◽  
pp. 639-642
Author(s):  
D. Nandagopal ◽  
J. Mazumdar ◽  
R.E. Bogner ◽  
G. Karolyi
Keyword(s):  
Heart Valve ◽  
Digital Processing ◽  
Heart Sounds

Rough Sets-Based Identification of Heart Valve Diseases Using Heart Sounds

2012 ◽  
pp. 667-676 ◽  
Author(s):  
Mostafa A. Salama ◽  
Aboul Ella Hassanien ◽  
Jan Platos ◽  
Aly A. Fahmy ◽  
Vaclav Snasel
Keyword(s):  
Heart Valve ◽  
Rough Sets ◽  
Heart Sounds ◽  
Heart Valve Diseases ◽  
Valve Diseases

Intelligent Stethoscope

2014 ◽  
Vol 3 (1) ◽  
pp. 73-80
Author(s):  
B Buvaneshwari ◽  
NA Rohinee ◽  
Sahana Roopkumar ◽  
Prabhu Ravikala Vittal
Keyword(s):  
Information System ◽  
Heart Valve ◽  
Heart Sound ◽  
Heart Sounds ◽  
Easy Access ◽  
The Internet ◽  
Sound Recording ◽  
Diseased Condition ◽  
Acoustic Recording ◽  
Modern Form

Heart valve disorders are primarily detected by auscultation, technique of listening to heart sounds. A more modern form of this technique is phonocardiography, concerned with the automated acoustic recording and processing of heart sounds.This paper presents a method that aims at development of an algorithm to detect common heart valve disorders by processing heart sounds and provision of easy access to patient data via the Internet. The proposed method uses thresholding techniques to determine certain criteria which can detect whether a heart sound recording belongs to a person suffering from valvular heart disease or not, by giving ‘diseased' or ‘not diseased' decisions (S. Ari, K. Sensharma, G. Saha, 2008). The recording in case of a ‘diseased' condition is transmitted to the hospital information system via the Internet, wherein it can be further analyzed by a doctor to diagnose the disease.

scholarly journals Heart Valve Stenosis Region Detection Algorithm on Heart Sounds

2012 ◽  
Vol 15 (11) ◽  
pp. 1330-1340 ◽  
Author(s):  
G.H. Lee ◽  
Y.J. Lee ◽  
M.N. Kim
Keyword(s):  
Heart Valve ◽  
Detection Algorithm ◽  
Heart Sounds ◽  
Region Detection

Support Vectors Machine-based identification of heart valve diseases using heart sounds

2009 ◽  
Vol 95 (1) ◽  
pp. 47-61 ◽  
Author(s):  
Ilias Maglogiannis ◽  
Euripidis Loukis ◽  
Elias Zafiropoulos ◽  
Antonis Stasis
Keyword(s):  
Heart Valve ◽  
Heart Sounds ◽  
Heart Valve Diseases ◽  
Support Vectors ◽  
Valve Diseases

SEGMENTATION OF HEART SOUNDS AND HEART MURMURS

2008 ◽  
Vol 08 (04) ◽  
pp. 549-559 ◽  
Author(s):  
L. HAMZA CHERIF ◽  
S. M. DEBBAL ◽  
F. BEREKSI-REGUIG
Keyword(s):  
Heart Valves ◽  
Average Duration ◽  
Digital Processing ◽  
Heart Sounds ◽  
Pathological Changes ◽  
Pathological Conditions ◽  
Primary Health ◽  
Heart Murmurs ◽  
Shannon Energy ◽  
Processing Techniques

Heart murmurs are often the first signs of pathological changes of the heart valves, and are usually found during auscultation in primary health care. Many pathological conditions of the cardiovascular system cause murmurs and aberrations in heart sounds. Phonocardiography provides the clinician with a complementary tool to record the heart sounds heard during auscultation. The advancement of intracardiac phonocardiography, combined with modern digital processing techniques, has strongly renewed researchers' interest in studying heart sounds and murmurs. This paper presents an algorithm for the detection of heart sounds (the first and second sounds, S1 and S2) and heart murmurs. The segmentation algorithm, which separates the heart signal (or the phonocardiogram (PCG) signal), is based on the normalized average Shannon energy of the PCG signal. This algorithm makes it possible to isolate individual sounds (S1 or S2) and murmurs to give an assessment of their average duration.

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