Higher-Order-Statistics-Based Fractal Dimension for Noisy Bowel Sound Detection

Author

Ming-Jen Sheu ; Ping-Yi Lin ; Jen-Yin Chen ; Chien-Ching Lee ; Bor-Shyh Lin

Author_Institution

Div. of Gastroenterology & Hepatology, Chi Mei Med. Center, Tainan, Taiwan

Volume

22

Issue

7

fYear

2015

fDate

Jul-15

Firstpage

789

Lastpage

793

Abstract

Bowel sounds is an important physiological parameter of distinguishing the gastrointestinal motility dysfunction. Auscultation of bowel sounds provides a noninvasive way for clinical diagnosis, but it is also easily affected by environmental noise. In this study, a novel higher-order-statistics (HOS)-based fractal dimension algorithm was proposed for detecting noisy bowel sounds. By using the nature of preserving non-Gaussianity for higher order statistics technique, the proposed method can effectively detect bowel sounds under different noise conditions, and its performance is insensitive to the change of noise type and noise level.

Keywords

acoustic signal detection; acoustic signal processing; bioacoustics; fractals; medical disorders; medical signal detection; medical signal processing; patient diagnosis; statistical analysis; auscultation; clinical diagnosis; environmental noise; gastrointestinal motility dysfunction; higher-order-statistics-based fractal dimension; noise level; noisy bowel sound detection; nonGaussianity nature; physiological parameter; Biomedical imaging; Electronic mail; Fractals; Higher order statistics; Noise; Noise measurement; Signal processing algorithms; Bowel sound; environmental noise; fractal dimension; higher order statistics;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2014.2369856

Filename

6952970