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Authors: Feng Jin 1 ; Farook Sattar 1 and Moe Pwint 2

Affiliations: 1 School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore ; 2 The University of Computer Studies, Singapore

Keyword(s): Noisy Respiratory Sound Signals, Phase Segmentation, Sample Entropy(SampEn), Genetic Algorithm (GA).

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: In this paper, a new approach to automatically segment noisy respiratory sound signals is proposed. Segmentation is formulated as an optimization problem and the boundaries of the signal segments are detected using a genetic algorithm (GA). As the estimated number of segments present in a segmenting signal is initially obtained, a multi-population GA is employed to determine the locations of segment boundaries. The segmentation results are found through the generations of GA by introducing a new evaluation function, which is based on the sample entropy and a heterogeneity measure. Illustrative results for respiratory sound signals contaminated by loud heartbeats and other high level noises show that the proposed genetic segmentation method is quite accurate and threshold independent to find the noisy respiratory segments as well as the pause segments under different noisy conditions.

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Paper citation in several formats:
Jin, F.; Sattar, F. and Pwint, M. (2008). PHASE SEGMENTATION OF NOISY RESPIRATORY SOUND SIGNALS USING GENETIC APPROACH. In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2008) - Volume 2: BIOSIGNALS; ISBN 978-989-8111-18-0; ISSN 2184-4305, SciTePress, pages 122-127. DOI: 10.5220/0001058001220127

@conference{biosignals08,
author={Feng Jin. and Farook Sattar. and Moe Pwint.},
title={PHASE SEGMENTATION OF NOISY RESPIRATORY SOUND SIGNALS USING GENETIC APPROACH},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2008) - Volume 2: BIOSIGNALS},
year={2008},
pages={122-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001058001220127},
isbn={978-989-8111-18-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2008) - Volume 2: BIOSIGNALS
TI - PHASE SEGMENTATION OF NOISY RESPIRATORY SOUND SIGNALS USING GENETIC APPROACH
SN - 978-989-8111-18-0
IS - 2184-4305
AU - Jin, F.
AU - Sattar, F.
AU - Pwint, M.
PY - 2008
SP - 122
EP - 127
DO - 10.5220/0001058001220127
PB - SciTePress