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A Novel Model for Screening Aortic Stenosis Using Phonocardiogram
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Linköping University, Linköping, Sweden .
Linköping University, Linköping, Sweden .
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1940-1747
Linköping University, Linköping, Sweden.
2015 (English)In: IFMBE Proceedings, Volume 48, Springer , 2015, Vol. 48, p. 48-51Conference paper, Published paper (Refereed)
Abstract [en]

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 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 , 2015. Vol. 48, p. 48-51
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-30481DOI: 10.1007/978-3-319-12967-9_13ISI: 000347893000013Scopus ID: 2-s2.0-84910656041ISBN: 978-3-319-12966-2 (print)OAI: oai:DiVA.org:mdh-30481DiVA, id: diva2:886147
Conference
16th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics and Medicinteknikdagarna Joint Conferences, NBC 2014 and MTD 2014; Gothenburg; Sweden; 14 October 2014 through 16 October 2014
Available from: 2015-12-21 Created: 2015-12-21 Last updated: 2020-10-21Bibliographically approved

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Lindén, Maria

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Citation style
  • apa
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