A Hybrid Model for Diagnosing Sever Aortic Stenosis in Asymptomatic Patients using Phonocardiogram
2015 (English)In: WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, 2015, VOLS 1 AND 2, Springer, 2015, Vol. 51, 1006-1009 p.Conference paper (Refereed)
This study presents a screening algorithm for severe aortic stenosis (AS), based on a processing method for phonocardiographic (PCG) signal. The processing method employs a hybrid model, constituted of a hidden Markov model and support vector machine. The method benefits from a preprocessing phase for an enhanced learning. The performance of the method is statistically evaluated using PCG signals recorded from 50 individuals who were referred to the echocardiography lab at Linkoping University hospital. All the individuals were diagnosed as having a degree of AS, from mild to severe, according to the echocardiographic measurements. The patient group consists of 26 individuals with severe AS, and the rest of the 24 patients comprise the control group. Performance of the method is statistically evaluated using repeated random sub sampling. Results showed a 95% confidence interval of (80.5%-82.8%)/(77.8%-80.8%) for the accuracy/sensitivity, exhibiting an acceptable performance to be used as decision support system in the primary healthcare center.
Place, publisher, year, edition, pages
Springer, 2015. Vol. 51, 1006-1009 p.
, IFMBE Proceedings, ISSN 1680-0737
Aortic stenosis; phonocardiogram; hybrid model; decision support; primary healthcare centers
Biomedical Laboratory Science/Technology
IdentifiersURN: urn:nbn:se:liu:diva-131738DOI: 10.1007/978-3-319-19387-8_245ISI: 000381813000245ISBN: 978-3-319-19387-8ISBN: 978-3-319-19386-1OAI: oai:DiVA.org:liu-131738DiVA: diva2:1002467
World Congress on Medical Physics and Biomedical Engineering