A Novel Model for Screening Aortic Stenosis Using Phonocardiogram
2015 (English)In: 16th Nordic-Baltic Conference on Biomedical Engineering / [ed] Henrik Mindedal and Mikael Persson, Springer Science Business Media , 2015, 48-51 p.Conference paper (Refereed)
This study presents an algorithm for screening aortic stenosis, based on heart sound signal processing. It benefits from an artificial intelligent-based (AI-based) model using a multi-layer perceptron neural network. The AI-based model learns disease related murmurs using non-stationary features of the murmurs. Performance of the model is statistically evaluated using two different databases, one of children and the other of elderly volunteers with normal heart condition and aortic stenosis. Results showed a 95% confidence interval of the high accuracy/sensitivity (84.1%-86.0%)/(86.0%-88.4%) thus exhibiting a superior performance to a cardiologist who relies on the conventional auscultation. The study suggests including the heart sound signal in the clinical decision making due to its potential to improve the screening accuracy.
Place, publisher, year, edition, pages
Springer Science Business Media , 2015. 48-51 p.
, IFMBE Proceedings, ISSN 1680-0737 ; 48
Aortic stenosis, phonocardiography, heart sound, heart murmurs
Biomedical Laboratory Science/Technology
IdentifiersURN: urn:nbn:se:liu:diva-112774DOI: 10.1007/978-3-319-12967-9_13ISI: 000347893000013ISBN: 978-3-319-12966-2 (Print)ISBN: 978-3-319-12967-9 (online)OAI: oai:DiVA.org:liu-112774DiVA: diva2:771830
16th Nordic-Baltic Conference on Biomedical Engineering, 16. NBC & 10. MTD 2014 joint conferences. October 14-16, 2014, Gothenburg, Sweden