Title :
Beat to Beat Classification of Long Electrocardiograms Using Entropies and Hierarchical Clustering
Author :
Bahmanyar, M.R. ; Balachandran, W.
Author_Institution :
Sch. of Eng., Brunel Univ., Middlesex
fDate :
6/27/1905 12:00:00 AM
Abstract :
This paper introduces an entropy based method for beat to beat classification of long electrocardiograms (ECGs). A state vector is reconstructed using Taken´s delay coordinates method and Shannon entropies are calculated for each beat to form feature vectors. Hierarchical clustering is applied to these vectors to classify the beats. The algorithm was used for detection of atrial premature beats and ventricular premature beats in long electrocardiograms
Keywords :
electrocardiography; entropy; medical signal processing; signal classification; signal reconstruction; ECG; Shannon entropy; Taken delay coordinates; atrial premature beat detection; beat-to-beat classification; hierarchical clustering; long electrocardiograms; state vector reconstruction; ventricular premature beat detection; Clustering algorithms; Continuous wavelet transforms; Delay effects; Design engineering; Electrocardiography; Entropy; Feature extraction; Finite impulse response filter; Frequency; Smoothing methods;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1615749
