An acoustical respiratory phase segmentation algorithm using genetic approach |
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Authors: | F. Jin F. Sattar D. Y. T. Goh |
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Affiliation: | (1) School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue 50, Singapore, 639798, Singapore;(2) Paediatrics Department, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore |
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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. |
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