Medical & Biological Engineering & Computing

, Volume 47, Issue 9, pp 941–953 | Cite as

An acoustical respiratory phase segmentation algorithm using genetic approach

Special Issue - Original Article
First Online:
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Accepted:

Abstract

This paper proposes a robust and fully automated respiratory phase segmentation method using single channel tracheal breath sounds (TBS) recordings of different types. The estimated number of respiratory segments in a TBS signal is firstly obtained based on noise estimation and nonlinear mapping. Respiratory phase boundaries are then located through the generations of multi-population genetic algorithm by introducing a new evaluation function based on sample entropy (SampEn) and a heterogeneity measure. The performance of the proposed method is analyzed for single channel TBS recordings of various types. An overall respiratory phase segmentation accuracy is found to be 12 ± 5 ms for normal TBS and 21 ± 9 ms for adventitious sounds. The results show the robustness and effectiveness of the proposed segmentation method. The proposed method has been a successful attempt to solve the clinical application challenge faced by the existing phase segmentation methods in terms of respiratory dysfunctions.

Keywords

Tracheal breath sound (TBS) Respiratory phase segmentation Multi-population genetic algorithm (GA) Sample entropy (SampEn) Heterogeneity measure 
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Notes

Acknowledgments

The authors gratefully acknowledge the contribution of National University Hospital, especially Dr. Irene Melinda Louis, for their support in data collection and identification. The authors are also grateful to the Reviewers and the Editor for their valuable comments and suggestions that help to improve the paper significantly.

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Copyright information

© International Federation for Medical and Biological Engineering 2009

Authors and Affiliations

  1. 1.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.Paediatrics Department, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore

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