New parameters for respiratory sound classification

In this paper, a new approach based on cepstral analysis is proposed to classify respiratory sounds. The sound signal is divided into segments, which are characterized by a reduced number of cepstral coefficients. Those segments are then classified as whether containing wheezes or normal respiratory sounds, by using the vector quantization (VQ) method. This approach is tested and compared to other kind of features extraction like the autoregressive representation and the wavelet transform.