DocumentCode :
3176935
Title :
Parameter optimization of awavelet-based electrocardiogram delineator with an evolutionary algorithm
Author :
Dumont, J. ; Hernández, A.I. ; Carrault, G.
Author_Institution :
Lab. Traitement du Signal et de l´´Image, Rennes I Univ.
fYear :
2005
fDate :
25-28 Sept. 2005
Firstpage :
707
Lastpage :
710
Abstract :
A recurrent problem encountered in many algorithms proposed to detect and segment ECG waves is the adjustment of the numerous parameters used. This work presents a method to optimize these parameters with an evolutionary algorithm (EA). The signal processing chain contains a filter to remove baseline wandering, a QRS detector (Pan & Tompkins) and a wave segmentation step based on the wavelet-transform (WT). The EA adjusts the parameters of the segmentation step in order to minimize the result of a cost function which measures how close the detector is from characteristic points annotated by a cardiologist. Results obtained with the QTDB are compared with other approaches of wave segmentation for which thresholds have been experimentally defined. EAs have shown to be an effective method to solve this complex problem of multiobjective optimization
Keywords :
electrocardiography; evolutionary computation; filtering theory; medical signal detection; medical signal processing; signal classification; wavelet transforms; ECG wave detection; ECG wave segmentation; QRS detector; baseline wandering removal; electrocardiogram delineator; evolutionary algorithm; filter; parameter optimization; signal processing; wavelet-transform; Bismuth; Cardiology; Cost function; Detectors; Electrocardiography; Evolutionary computation; Filter bank; Information resources; Optimization methods; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology, 2005
Conference_Location :
Lyon
Print_ISBN :
0-7803-9337-6
Type :
conf
DOI :
10.1109/CIC.2005.1588202
Filename :
1588202
Link To Document :
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