DocumentCode :
35925
Title :
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
Link To Document :
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