Detection Of QRS-Wave In Electrocardiogram: Based On Kalman And Wavelets

Author

Chen, Yu ; Yan, Zhuangzhi ; He, Weixin

Author_Institution

Sch. of Commun. & Inf. Eng., Shanghai Univ.

fYear

2006

Firstpage

2758

Lastpage

2760

Abstract

An algorithm using wavelets and Kalman filtering method has been developed for QRS detection. The algorithm takes following steps: i) We use a RLS adaptive algorithm to establish a model of the electrocardiogram. Thus the algorithm can change its own model according to the change of the electrocardiogram, ii) Based on the model established in stage i), we combined the wavelet and Kalman algorithm, decomposed the signal to several scales, filtering the signal in each scale. And then, iii) A decision rule is used to determine the QRS complex. The method was tested on ECG data form the MIT database, and experimental results show that the method is effective, and the influence of the noise can be eliminated

Keywords

Kalman filters; electrocardiography; medical signal detection; medical signal processing; Kalman filtering; QRS-wave detection; RLS adaptive algorithm; decision rule; electrocardiogram; signal decomposition; signal filtering; wavelets; Adaptive algorithm; Cardiac disease; Change detection algorithms; Electrocardiography; Filtering algorithms; Kalman filters; Resonance light scattering; Time series analysis; Wavelet transforms; Working environment noise; ECG; Kalman algorithm; QRS complex; wavelets;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IEMBS.2005.1617043

Filename

1617043