Automated classification of lung sound signals based on empirical mode decomposition

作者：

Highlights：

• The proposed method efficiently classifies chronic and non-chronic lung sounds.

• The classification accuracy achieved out performed state-of-the-art.

• The time domain computation makes it suitable for real time expert system.

摘要

•The proposed method efficiently classifies chronic and non-chronic lung sounds.•The classification accuracy achieved out performed state-of-the-art.•The time domain computation makes it suitable for real time expert system.

论文关键词：Empirical mode decomposition (EMD),Intrinsic mode function (IMF),Two-dimensional phase space representation (2D-PSR),Higher- dimensional phase space representation (HD-PSR),Neighborhood component analysis (NCA),Ensemble of bagged trees

论文评审过程：Received 26 October 2020, Revised 13 June 2021, Accepted 19 June 2021, Available online 26 June 2021, Version of Record 19 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115456