An intelligent method for discrimination between aortic and pulmonary stenosis using phonocardiogram

• This study presents an artificial intelligent-based method for processing phonocardiographic (PCG) signal of the patients with ejection murmur to assess the underlying pathology initiating the murmur. The method is based on our unique method for finding disease-related frequency bands in conjunction with a sophisticated statistical classifier. Children with aortic stenosis (AS), and pulmonary stenosis (PS) were the two patient groups subjected to the study, taking the healthy ones (no murmur) as the control group. PCG signals were acquired from 45 referrals to the children University hospital, comprised of 15 individuals of each group; all were diagnosed by the expert pediatric cardiologists according to the echocardiographic measurements together with the complementary tests. The accuracy of the method is evaluated to be 90% and 93.3% using the 5-fold and leave-one-out validation method, respectively. The accuracy is slightly degraded to 86.7% and 93.3% when a Gaussian noise with signal to noise ratio of 20 dB is added to the PCG signals, exhibiting an acceptable immunity against the noise. The method offered promising results to be used as a decision support system in the primary healthcare centers or clinics.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

Aortic stenosis

Decision support system

Phonocardiogram

Primary healthcare centers

Pulmonary stenosis

Artificial intelligence

Biomedical engineering

Blood vessels

Classification (of information)

Diseases

Frequency bands

Gaussian noise (electronic)

Health care

Medicine

Phonocardiography

Signal to noise ratio

Artificial intelligent

Control groups

Intelligent method

Phonocardiograms

Primary healthcare

Statistical classifier

Decision support systems

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)