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2013, vol. 14, br. 3, str. 113-120
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Fonokardiografska detekcija prolapsa mitralne valvule upotrebom arteficijalne neuronske mreže
Phonocardiography-based mitral valve prolapse detection using an artificial neural network
aKliničko-bolnički centar Zvezdara, Beograd, Srbija bUniverzitet u Beogradu, Elektrotehnički fakultet, Katedra za telekomunikacije, Srbija cUniverzitet u Beogradu, Elektrotehnički fakultet, Inovacioni centar za informacione tehnologije, Srbija dUniverzitet u Kragujevcu, Ekonomski fakultet, Srbija eUniverzitet u Kragujevcu, Fakultet medicinskih nauka, Katedra za fiziologiju, Srbija
e-adresa: drvladakgbg@yahoo.com
Projekat: Efekti homocisteina i homocisteinu srodnih supstanci na kardiovaskularni sistem: Uloga gasnih transmitera NO, H2S I CO (MPNTR - 175043)
Keywords: phonocardiography - mitral valve prolapse-neural network
Sažetak
Prolaps mitralne valvule (MVP) je najčešća anomalija zalistaka i najčešći uzrok izolovane mitralne insuficijencije. MVP ima najpovoljniji tok i prognozu u detinjstvu, dok komplikacije kao što su teška mitralna regurgitacija, infektivni miokarditis, embolija pluća, aritmija i iznenadna smrt se češće javljaju kod starijih ljudi, što zahteva brzu dijagnostiku i prevenciju. Usled učestalog javljanja, otežane dijagnostike i kliničkog značaja ranog otkrivanja MVP, cilj ove studije je bio da razvije originalni, neinvazivni i lako primenljiv dijagnostički metod za otkrivanje MVP kod dece i adolescenata upotrebom arteficijalne neuronske mreže (ANN). Srčani tonovi kod 48 dece sa MVP, 49 zdrave dece i 38 dece sa patološkim srčanim šumovima nastalim usled atrijalnog septalnog defekta (ASD), ventrikularnog septalnog defekta (VSD), duktus arteriosus persistensaotvorenog arterijskog kanala (DAP), aortne stenoze (AS), stenoze plućne arterije (PS), koarktacije aorte (ACo), mitralne regurgitacije (MR), mitralne insuficijencije (MI) i trikuspidalne insuficijencije (TI) su zabeleženi auskultacijom upotrebom elektronskimog stetoskopopa. U elektronskom stetoskopu zvuk se snima na unutrašnjoj memoriji stetoskopa a potom pomoću transmitera prenosi na memoriju kompjutera. Osnovni softver za proveru i analizu zvuka se nalazi u sklopu elektronskog stetoskopa i omogućava fonokardiografsku i spektralnu prezentaciju auskultatornog nalaza. U daljoj kvalitativnoj analizi, fonokardiogram u digitalnom obliku (format *.e4k) se prevodi u standard *.wav format, koji je prvi korak u obradi digitalnog signala, proučavanju i testiranju ANN. Dobijena preciznost svrstavanja MVP u odgovarajuću kategoriju je bila 71.2%. Ovi rezultati mogu biti interesantni u fonokardiografskoj dijagnostici MVP kod dece i adolescenata.
Abstract
Mitral valve prolapse (MVP) is the most common valve anomaly and the most frequent cause of isolated mitral insufficiency. MVP has a mostly benign course and prognosis in childhood; however, complications, such as severe mitral regurgitation, infectious endocarditis, pulmonary embolism, arrhythmia and sudden death, occur more often in elderly people, demonstrating the need for prompt diagnostics and prevention. Due to its frequent occurrence, failures in diagnosing MVP and the clinical importance of early MVP detection, the aim of this study was to develop an original, non-invasive and easily applicable diagnostic method for MVP detection in children and adolescents by using an artificial neural network (ANN). Cardiac sounds were recorded by auscultation using electronic stethoscope in 48 children with MVP, 49 healthy children and 38 children with a pathological heart murmur from atrial septal defect (ASD), ventricular septal defect (VSD), ductus arteriosus persistence (DAP), aortic stenosis (AS), pulmonic stenosis (PS), aortic coarctation (ACo), mitral regurgitation (MR), mitral insufficiency (MI) and tricuspid insufficiency (TI). In electronic stethoscopes, the sound is archived in the internal memory of the stethoscope and then transmitted to a computer by a transmitter. Basic software for the check-up and sound analysis is provided along with the electronic stethoscopes and provides a phonocardiograph and spectral presentation of auscultative findings. For further qualitative analysis, the digital form (format *.e4k) of the phonocardiogram is transformed into standard *.wav format, which is the first step in the processing of the digital signal for studying and testing with an ANN. The obtained precision of MVP classification category was 71.2%. These results may be interesting for the phonocardiograph diagnosis of MVP in children and adolescents.
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