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Arteriovenous fistula stenosis detection using wavelets and support vector machines

Vasquez Obando, Pablo LU ; Munguia Mena, Marco LU and Mandersson, Bengt LU (2009) Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009 In [Host publication title missing] p.1298-1301
Abstract
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.
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
[Host publication title missing]
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
external identifiers
  • scopus:77951009607
ISSN
1557-170X
ISBN
978-1-4244-3296-7
DOI
10.1109/IEMBS.2009.5332592
language
English
LU publication?
yes
id
29889bd2-3ae5-419f-8ac6-58295ca24539 (old id 1670904)
date added to LUP
2010-09-15 13:44:48
date last changed
2017-11-19 03:47:02
@inproceedings{29889bd2-3ae5-419f-8ac6-58295ca24539,
  abstract     = {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.},
  author       = {Vasquez Obando, Pablo and Munguia Mena, Marco and Mandersson, Bengt},
  booktitle    = {[Host publication title missing]},
  isbn         = {978-1-4244-3296-7},
  issn         = {1557-170X},
  language     = {eng},
  pages        = {1298--1301},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Arteriovenous fistula stenosis detection using wavelets and support vector machines},
  url          = {http://dx.doi.org/10.1109/IEMBS.2009.5332592},
  year         = {2009},
}