Classification of normalized healty and pathological lung sounds

In this paper, lung sounds were classified as healthy and pathological. Means and standard deviations of Mel Frequency Cepstrum Coefficients were used as features and also parameters obtained by exponential curve fitted to these values.

Optimum performance obtained as 92.65% when exponential curve fit parameters used for the average of Mel Frequency Cepstrum Coefficients. k-Nearest Neighbor algorithm were used in the classification process.

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