Analysis and classification of respiratory sounds by signal coherence method

In this study, the application of signal coherence method for parametric representation and automatic classification of the respiratory sounds is investigated. Signal coherence is a measure of spectral stability of signals both in terms of amplitude and phase and it basically compares a mean spectrum of the signal which is assumed to be constant throughout the signal and the amount of variation around this mean spectrum.

[1]  Alan V. Oppenheim,et al.  Discrete-Time Signal Pro-cessing , 1989 .

[2]  Anil K. Jain,et al.  Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  H. Pasterkamp,et al.  Respiratory sounds. Advances beyond the stethoscope. , 1997, American journal of respiratory and critical care medicine.

[4]  N Gavriely,et al.  Parametric representation of normal breath sounds. , 1992, Journal of applied physiology.

[5]  M. Hinich,et al.  A statistical theory of signal coherence , 2000, IEEE Journal of Oceanic Engineering.

[6]  A. K. Majumder,et al.  Digital Spectrum Analysis of Respiratory Sound , 1981, IEEE Transactions on Biomedical Engineering.

[7]  F. Dalmasso,et al.  Definition of terms for applications of respiratory sounds , 2000 .