Investigation of complexity of extraction accuracy modeling cardio signals in two ways

Author

Kersulyte, Gintare ; Navickas, Zenonas ; Raudonis, Vidas

Author_Institution

Kaunas Univ. of Technol., Kaunas, Lithuania

fYear

2009

fDate

21-23 Sept. 2009

Firstpage

462

Lastpage

467

Abstract

How to extract information intensively from cardio signals for the diagnosis of diseases and assessment of heart function is a topical subject. Heart is not a periodic oscillator under normal physiologic conditions and standard linear measures may not be able to detect subtle, but important changes in heart time series, whereas, most of nonlinear measures suffer from the curse of dimensionally. In this paper, we show the results of cardio signals identification using the proposed structure based on H rank function employment.

Keywords

Hankel matrices; diseases; electrocardiography; feature extraction; medical diagnostic computing; medical signal processing; physiology; principal component analysis; time series; H rank function; Hankel matrix; cardio signal identification; cardio signal modeling; disease diagnosis; electrocardiogram analysis; heart function; heart time series; information extraction; physiologic condition; principal component analysis; signal processing; Cardiac disease; Cardiology; Cardiovascular diseases; Data mining; Employment; Heart; Measurement standards; Oscillators; Signal processing; Time measurement; Hankel rank; exponential function; polynomial function; signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2009. IDAACS 2009. IEEE International Workshop on

Conference_Location

Rende

Print_ISBN

978-1-4244-4901-9

Electronic_ISBN

978-1-4244-4882-1

Type

conf

DOI

10.1109/IDAACS.2009.5342938

Filename

5342938