mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Forth heart sound detection using backward time-growing neural network
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
CAPIS Biomedical Research and Development Centre, Mon, Belgium.
Linköping University.
2020 (English)In: IFMBE Proceedings, Springer Verlag , 2020, p. 341-345Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel method for processing heart sound signal for screening forth heart sound (S4). The proposed method is based on time growing neural network with a new scheme, which we call the Backward Time-Growing Neural Network (BTGNN). The BTGNN is trained for detecting S4 in recordings of heart sound signal. In total, 83 children patients, referred to a children University hospital, participated in the study. The collected signals are composed of the subjects with and without S4 for training and testing the method. Performance of the method is evaluated using the Leave-One-Out and the repeated random sub sampling methods. The accuracy/sensitivity of the method is estimated to be 88.3%/82.4% and the structural risk is calculated to be 18.3% using repeated random sub sampling and the A-Test methods, respectively.

Place, publisher, year, edition, pages
Springer Verlag , 2020. p. 341-345
Keywords [en]
A-Test method, Backward time-growing neural network, Intelligent phonocardiography, Time-growing neural network, Biochemical engineering, Diagnosis, Heart, Phonocardiography, Risk perception, Testing, Backward time, Heart sound signal, Leave one out, Structural risks, Sub-sampling, Sub-sampling methods, Test method, Training and testing, Cardiology
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-43874DOI: 10.1007/978-3-030-17971-7_53Scopus ID: 2-s2.0-85066034972ISBN: 9783030179700 (print)OAI: oai:DiVA.org:mdh-43874DiVA, id: diva2:1323100
Conference
International Conference on Medical and Biological Engineering in Bosnia and Herzegovina, CMBEBIH 2019, 16 May 2019 through 18 May 2019
Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2019-06-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Ghareh Baghi, Arash

Search in DiVA

By author/editor
Ghareh Baghi, Arash
By organisation
Embedded Systems
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 43 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf