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Arteriovenous fistula stenosis detection using wavelets and support vector machines

Author

  • Pablo Vasquez Obando
  • Marco Munguia Mena
  • Bengt Mandersson

Summary, in English

The objective of this exploratory study was to develop signal processing methods for assisting in the diagnosis of arteriovenous fistula stenosis on patients suffering from end-stage renal disease and undergoing haemodialysis treatments. The proposed method is based on the classification of vessels sounds utilizing parameter extraction from wavelets transform coefficients. The coefficients energy of selected scales (frequency bands) were fed to a support vector machine based system for classification. Results suggested that this technique can be useful for diagnosis purposes to physicians during the auscultation procedure.

Publishing year

2009

Language

English

Pages

1298-1301

Publication/Series

[Host publication title missing]

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Electrical Engineering, Electronic Engineering, Information Engineering

Conference name

Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009

Conference date

2009-09-03 - 2009-09-06

Conference place

Minneapolis, Minnesota, United States

Status

Published

Research group

  • Signal Processing Group
  • Signal Processing

ISBN/ISSN/Other

  • ISSN: 1557-170X
  • ISBN: 978-1-4244-3296-7