The analysis of heart sounds based on linear and high order statistical methods

Author

Ergen, Burhan ; Tatar, Yetkin

Author_Institution

Dept. of Comput. Eng., Firat Univ., Elazig, Turkey

Volume

3

fYear

2001

fDate

2001

Firstpage

2139

Abstract

This paper investigates the applicability of high order statistical autoregressive (AR-HOS) modeling method in analyzing biomedical signals. The autoregressive (AR) method using linear prediction and AR-HOS method using cumulants; are applied on normal and pathological heart sound signals. It is found that the AR-HOS modeling a signal produce a more accurate and higher resolution spectrum than AR modeling.

Keywords

acoustic signal processing; bioacoustics; cardiology; medical signal processing; statistical analysis; audible heart sounds; biomedical signals analysis; cumulants; heart disease detection; high order statistical autoregressive modeling method; more accurate higher resolution spectrum; normal heart sound signals; parametric modeling methods; pathological heart sound signals; signal modeling; Acoustic noise; Autocorrelation; Biological system modeling; Frequency estimation; Heart; Parametric statistics; Signal analysis; Signal processing; Statistical analysis; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1017178

Filename

1017178