Title :
Application of the Empirical Mode Decomposition in the study of murmurs from Arteriovenous fistula stenosis
Author :
Pablo Vásquez;Munguía M. Marco;Elisabeth Mattsson;Bengt Mandersson
Author_Institution :
UNI-Asdi-FEC Group, Faculty of Electrical Engineering and Computer Science, National University of Engineering, Managua, Nicaragua
Abstract :
The Empirical Mode Decomposition (EMD) is a method to decompose non linear, non stationary time series into a sum of different modes, named Intrinsical Mode Functions each one having a characteristic frequency. In the present work we used the EMD to investigate the properties of the recorded sounds from the Arteriovenous fistula on hemodialysis patients. Phonoangiographic signals coming from two different vessel conditions, stenotic and non-stenotic, were analyzed by using EMD, the mean energy and mean instantaneous frequency per IMF proved to be good features for classification. Three types of classification schemes were tested on data from the first IMf features achieving good results.
Keywords :
"Feature extraction","Time frequency analysis","Blood","Artificial neural networks","Conferences","Oscillators","Hospitals"
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Print_ISBN :
978-1-4244-4123-5
Electronic_ISBN :
1558-4615
DOI :
10.1109/IEMBS.2010.5627552