Pitch Synchronous Wavelet and Hidden Semi-Markov Models based method for ECG analysis

Author

Krimi, Samar ; Ouni, Kais ; Ellouze, Noureddine

Author_Institution

Lab. of Syst. & Signal Process. (LSTS), Nat. Eng. Sch. of Tunis (ENIT), Tunis, Tunisia

fYear

2007

fDate

3-7 Sept. 2007

Firstpage

1407

Lastpage

1411

Abstract

In this paper we develop a new approach to ECG analysis, combining Pitch Synchronous Wavelet Transform (PSWT) and Hidden Semi-Markov Model (HSMM) for tracking the typical ECG cycle. The combination of these two techniques was examined in a way that the PSWT of an ECG signal was an input for the HSMM. This approach was tested and evaluated on the manually annotated QT database. Experimental results show the accuracy of the proposed technique for all corrupted ECG tested reaching a sensitivity Se=99,95% for QRS detection and Se=97,79% for T detection.

Keywords

electrocardiography; hidden Markov models; medical signal detection; medical signal processing; synchronisation; tracking; wavelet transforms; ECG analysis; ECG signal PSWT; HSMM input; QRS detection sensitivity; T detection; corrupted ECG testing; hidden semi-Markov model based method; manually annotated QT database; pitch synchronous wavelet based method; pitch synchronous wavelet transform; typical ECG cycle tracking; Databases; Electrocardiography; Hidden Markov models; Markov processes; Signal processing; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2007 15th European

Conference_Location

Poznan

Print_ISBN

978-839-2134-04-6

Type

conf

Filename

7099037