Arteriovenous fistula stenosis detection using wavelets and support vector machines
Publikation/Tidskrift/Serie: [Host publication title missing]
Förlag: IEEE--Institute of Electrical and Electronics Engineers Inc.
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.
- Electrical Engineering, Electronic Engineering, Information Engineering
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
- Signal Processing Group-lup-obsolete
- Signal Processing-lup-obsolete
- ISSN: 1557-170X
- ISBN: 978-1-4244-3296-7