Abstract
This study describes a method of quantitatively characterizing cough sounds using digital signal processing techniques. Differences between asthmatic and non-asthmatic cough sounds are presented. Coughs from 12 asthmatic and 5 non-asthmatic subjects were analysed. Cough sounds and flows were digitized, at a sampling rate of 5 kHz, before and after a free-running exercise test. Individual coughs were divided into two or three phases, corresponding to the initial glottal opening burst, the quieter middle phase, and (sometimes) the final closing burst. Standard signal processing techniques were then invoked to characterize the spectral and temporal shapes of the first two phases. Factor analysis indicated that the spectral shapes of the two phases are independent, with each being largely described by the degree of "peakedness" in the spectrum, and by the balance of energy between low and high frequencies. Both the duration of the initial burst and zero-crossing rates of the cough waveform (which indicates the "spectral balance") during each of the first two phases were smaller for asthmatic than for non-asthmatic coughs. Fewer asthmatic coughs contained a final burst. Discriminant analysis between the two groups gave classification error rates of 20-30%. The peak flow recorded during the cough was significantly smaller for asthmatics, and correlated very well with the peak flow recorded during forced expiration. Thus, significant differences exist between asthmatic and non-asthmatic cough sounds. An effective representation of the temporal structure of the cough sound is required to successfully characterize the cough.
